Airbnb in Paris

Dataset statistics

Number of variables	50
Number of observations	50133
Missing cells	71154
Missing cells (%)	2.8%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	88.7 MiB
Average record size in memory	1.8 KiB

Variable types

Numeric	15
Categorical	34
DateTime	1

Alerts

`host_acceptance_rate` has a high cardinality: 100 distinct values	High cardinality
`host_neighbourhood` has a high cardinality: 235 distinct values	High cardinality
`neighbourhood` has a high cardinality: 220 distinct values	High cardinality
`host_listings_count` is highly correlated with `host_total_listings_count` and 1 other fields	High correlation
`host_total_listings_count` is highly correlated with `host_listings_count` and 1 other fields	High correlation
`accommodates` is highly correlated with `bedrooms` and 2 other fields	High correlation
`bedrooms` is highly correlated with `accommodates` and 1 other fields	High correlation
`beds` is highly correlated with `accommodates` and 1 other fields	High correlation
`price` is highly correlated with `accommodates`	High correlation
`maximum_nights` is highly correlated with `long_term_stays`	High correlation
`calculated_host_listings_count` is highly correlated with `host_listings_count` and 1 other fields	High correlation
`calculated_host_listings_count_entire_homes` is highly correlated with `calculated_host_listings_count_private_rooms`	High correlation
`calculated_host_listings_count_private_rooms` is highly correlated with `calculated_host_listings_count_entire_homes`	High correlation
`bed_linen` is highly correlated with `coffee_machine`	High correlation
`coffee_machine` is highly correlated with `bed_linen` and 1 other fields	High correlation
`cooking_basics` is highly correlated with `coffee_machine`	High correlation
`long_term_stays` is highly correlated with `maximum_nights`	High correlation
`host_listings_count` is highly correlated with `host_total_listings_count`	High correlation
`host_total_listings_count` is highly correlated with `host_listings_count`	High correlation
`accommodates` is highly correlated with `bedrooms` and 1 other fields	High correlation
`bedrooms` is highly correlated with `accommodates` and 1 other fields	High correlation
`beds` is highly correlated with `accommodates` and 1 other fields	High correlation
`calculated_host_listings_count` is highly correlated with `calculated_host_listings_count_entire_homes`	High correlation
`calculated_host_listings_count_entire_homes` is highly correlated with `calculated_host_listings_count`	High correlation
`bed_linen` is highly correlated with `coffee_machine`	High correlation
`coffee_machine` is highly correlated with `bed_linen` and 1 other fields	High correlation
`cooking_basics` is highly correlated with `coffee_machine`	High correlation
`id` is highly correlated with `host_is_superhost` and 14 other fields	High correlation
`host_is_superhost` is highly correlated with `id` and 17 other fields	High correlation
`host_listings_count` is highly correlated with `host_identity_verified` and 13 other fields	High correlation
`host_total_listings_count` is highly correlated with `host_identity_verified` and 13 other fields	High correlation
`host_identity_verified` is highly correlated with `id` and 20 other fields	High correlation
`accommodates` is highly correlated with `number_of_reviews_l30d` and 10 other fields	High correlation
`bedrooms` is highly correlated with `id` and 17 other fields	High correlation
`beds` is highly correlated with `number_of_reviews_l30d` and 10 other fields	High correlation
`price` is highly correlated with `number_of_reviews_l30d` and 9 other fields	High correlation
`minimum_nights` is highly correlated with `number_of_reviews_l30d` and 16 other fields	High correlation
`maximum_nights` is highly correlated with `number_of_reviews_l30d` and 13 other fields	High correlation
`availability_90` is highly correlated with `number_of_reviews_l30d` and 10 other fields	High correlation
`number_of_reviews` is highly correlated with `number_of_reviews_l30d` and 12 other fields	High correlation
`number_of_reviews_l30d` is highly correlated with `id` and 24 other fields	High correlation
`instant_bookable` is highly correlated with `host_is_superhost` and 20 other fields	High correlation
`calculated_host_listings_count` is highly correlated with `host_is_superhost` and 15 other fields	High correlation
`calculated_host_listings_count_entire_homes` is highly correlated with `calculated_host_listings_count_private_rooms` and 9 other fields	High correlation
`calculated_host_listings_count_private_rooms` is highly correlated with `id` and 29 other fields	High correlation
`air_conditioning` is highly correlated with `id` and 25 other fields	High correlation
`bed_linen` is highly correlated with `host_is_superhost` and 11 other fields	High correlation
`breakfast` is highly correlated with `id` and 29 other fields	High correlation
`tv` is highly correlated with `id` and 18 other fields	High correlation
`coffee_machine` is highly correlated with `host_identity_verified` and 10 other fields	High correlation
`cooking_basics` is highly correlated with `minimum_nights` and 10 other fields	High correlation
`white_goods` is highly correlated with `id` and 28 other fields	High correlation
`elevator` is highly correlated with `id` and 24 other fields	High correlation
`parking` is highly correlated with `id` and 25 other fields	High correlation
`host_greeting` is highly correlated with `id` and 29 other fields	High correlation
`internet` is highly correlated with `id` and 29 other fields	High correlation
`long_term_stays` is highly correlated with `id` and 29 other fields	High correlation
`private_entrance` is highly correlated with `id` and 29 other fields	High correlation
`review_scores_checkin` is highly correlated with `review_scores_accuracy` and 7 other fields	High correlation
`host_acceptance_rate` is highly correlated with `instant_bookable`	High correlation
`instant_bookable` is highly correlated with `host_acceptance_rate`	High correlation
`review_scores_accuracy` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`bed_linen` is highly correlated with `coffee_machine`	High correlation
`host_response_rate` is highly correlated with `host_response_time`	High correlation
`review_scores_rating` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`coffee_machine` is highly correlated with `bed_linen` and 1 other fields	High correlation
`time_since_last_review` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`review_scores_location` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`property_type` is highly correlated with `room_type`	High correlation
`bathrooms_text` is highly correlated with `room_type`	High correlation
`review_scores_communication` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`review_scores_value` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`host_response_time` is highly correlated with `host_response_rate`	High correlation
`cooking_basics` is highly correlated with `coffee_machine`	High correlation
`time_since_first_review` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`review_scores_cleanliness` is highly correlated with `review_scores_checkin` and 7 other fields	High correlation
`room_type` is highly correlated with `property_type` and 1 other fields	High correlation
`id` is highly correlated with `time_since_first_review`	High correlation
`host_response_time` is highly correlated with `host_response_rate` and 2 other fields	High correlation
`host_response_rate` is highly correlated with `host_response_time` and 4 other fields	High correlation
`host_acceptance_rate` is highly correlated with `host_response_time` and 7 other fields	High correlation
`host_listings_count` is highly correlated with `host_response_rate` and 4 other fields	High correlation
`host_total_listings_count` is highly correlated with `host_response_rate` and 4 other fields	High correlation
`property_type` is highly correlated with `room_type` and 3 other fields	High correlation
`room_type` is highly correlated with `property_type` and 2 other fields	High correlation
`accommodates` is highly correlated with `bathrooms_text` and 1 other fields	High correlation
`bathrooms_text` is highly correlated with `property_type` and 6 other fields	High correlation
`bedrooms` is highly correlated with `bathrooms_text` and 1 other fields	High correlation
`beds` is highly correlated with `bathrooms_text` and 1 other fields	High correlation
`price` is highly correlated with `accommodates` and 1 other fields	High correlation
`availability_90` is highly correlated with `host_response_time` and 1 other fields	High correlation
`number_of_reviews` is highly correlated with `number_of_reviews_l30d`	High correlation
`number_of_reviews_l30d` is highly correlated with `number_of_reviews`	High correlation
`review_scores_rating` is highly correlated with `review_scores_accuracy` and 7 other fields	High correlation
`review_scores_accuracy` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`review_scores_cleanliness` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`review_scores_checkin` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`review_scores_communication` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`review_scores_location` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`review_scores_value` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`instant_bookable` is highly correlated with `host_acceptance_rate`	High correlation
`calculated_host_listings_count` is highly correlated with `host_acceptance_rate` and 3 other fields	High correlation
`calculated_host_listings_count_entire_homes` is highly correlated with `host_acceptance_rate` and 3 other fields	High correlation
`calculated_host_listings_count_private_rooms` is highly correlated with `host_acceptance_rate` and 2 other fields	High correlation
`air_conditioning` is highly correlated with `property_type` and 1 other fields	High correlation
`bed_linen` is highly correlated with `coffee_machine` and 1 other fields	High correlation
`coffee_machine` is highly correlated with `bed_linen` and 2 other fields	High correlation
`cooking_basics` is highly correlated with `bed_linen` and 1 other fields	High correlation
`parking` is highly correlated with `coffee_machine`	High correlation
`time_since_first_review` is highly correlated with `id` and 8 other fields	High correlation
`time_since_last_review` is highly correlated with `review_scores_rating` and 7 other fields	High correlation
`host_acceptance_rate` has 25900 (51.7%) missing values	Missing
`host_neighbourhood` has 13528 (27.0%) missing values	Missing
`neighbourhood` has 20064 (40.0%) missing values	Missing
`first_review` has 11423 (22.8%) missing values	Missing
`bedrooms` is highly skewed (γ1 = 25.28348159)	Skewed
`beds` is highly skewed (γ1 = 22.19124469)	Skewed
`maximum_nights` is highly skewed (γ1 = 223.8081539)	Skewed
`number_of_reviews_l30d` is highly skewed (γ1 = 50.49864021)	Skewed
`id` has unique values	Unique
`host_listings_count` has 8245 (16.4%) zeros	Zeros
`host_total_listings_count` has 8245 (16.4%) zeros	Zeros
`beds` has 1333 (2.7%) zeros	Zeros
`availability_90` has 28647 (57.1%) zeros	Zeros
`number_of_reviews` has 11423 (22.8%) zeros	Zeros
`number_of_reviews_l30d` has 41484 (82.7%) zeros	Zeros
`calculated_host_listings_count_entire_homes` has 7846 (15.7%) zeros	Zeros
`calculated_host_listings_count_private_rooms` has 41509 (82.8%) zeros	Zeros

Reproduction

Analysis started	2021-12-27 01:51:59.132715
Analysis finished	2021-12-27 02:02:11.397551
Duration	10 minutes and 12.26 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	50133
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25941992.23

Minimum	5396
Maximum	52166001
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	5396
5-th percentile	2395069.8
Q1	12146136
median	25444250
Q3	40048250
95-th percentile	50534752
Maximum	52166001
Range	52160605
Interquartile range (IQR)	27902114

Descriptive statistics

Standard deviation	15666125.14
Coefficient of variation (CV)	0.6038905955
Kurtosis	-1.285013236
Mean	25941992.23
Median Absolute Deviation (MAD)	13993465
Skewness	0.03211710919
Sum	1.300549896 × 10¹²
Variance	2.454274767 × 10¹⁴
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5396	1	< 0.1%
35740970	1	< 0.1%
35713954	1	< 0.1%
35722216	1	< 0.1%
35723796	1	< 0.1%
35725455	1	< 0.1%
35728169	1	< 0.1%
35730177	1	< 0.1%
35730913	1	< 0.1%
35731566	1	< 0.1%
Other values (50123)	50123	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5396	1	< 0.1%
7397	1	< 0.1%
7964	1	< 0.1%
9359	1	< 0.1%
9952	1	< 0.1%
10586	1	< 0.1%
10588	1	< 0.1%
10917	1	< 0.1%
11213	1	< 0.1%
11265	1	< 0.1%

Value	Count	Frequency (%)
52166001	1	< 0.1%
52165011	1	< 0.1%
52163316	1	< 0.1%
52162674	1	< 0.1%
52162381	1	< 0.1%
52161127	1	< 0.1%
52161033	1	< 0.1%
52160741	1	< 0.1%
52159958	1	< 0.1%
52159765	1	< 0.1%

host_response_time
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.3 MiB

unknown	26839
within an hour	12539
within a few hours	4977
within a day	4264
a few days or more	1514

Length

Max length	18
Median length	7
Mean length	10.60030319
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	within an hour
2nd row	within an hour
3rd row	within a day
4th row	within an hour
5th row	within an hour

Common Values

Value	Count	Frequency (%)
unknown	26839	53.5%
within an hour	12539	25.0%
within a few hours	4977	9.9%
within a day	4264	8.5%
a few days or more	1514	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
unknown	26839	25.6%
within	21780	20.8%
an	12539	12.0%
hour	12539	12.0%
a	10755	10.3%
few	6491	6.2%
hours	4977	4.8%
day	4264	4.1%
days	1514	1.4%
or	1514	1.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_response_rate
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.3 MiB

unknown	26839
100%	14460
50-89%	3735
90-99%	3145
0-49%	1954

Length

Max length	7
Median length	7
Mean length	5.919514093
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	100%
2nd row	100%
3rd row	50-89%
4th row	100%
5th row	100%

Common Values

Value	Count	Frequency (%)
unknown	26839	53.5%
100%	14460	28.8%
50-89%	3735	7.5%
90-99%	3145	6.3%
0-49%	1954	3.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
unknown	26839	53.5%
100	14460	28.8%
50-89	3735	7.5%
90-99	3145	6.3%
0-49	1954	3.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_acceptance_rate
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	100
Distinct (%)	0.4%
Missing	25900
Missing (%)	51.7%
Memory size	2.2 MiB

100%	8446
0%	1990
98%	1356
99%	948
50%	820
Other values (95)	10673

Length

Max length	4
Median length	3
Mean length	3.264845459
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	89%
2nd row	80%
3rd row	0%
4th row	20%
5th row	100%

Common Values

Value	Count	Frequency (%)
100%	8446	16.8%
0%	1990	4.0%
98%	1356	2.7%
99%	948	1.9%
50%	820	1.6%
67%	600	1.2%
97%	580	1.2%
96%	550	1.1%
93%	460	0.9%
95%	445	0.9%
Other values (90)	8038	16.0%
(Missing)	25900	51.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
100	8446	34.9%
0	1990	8.2%
98	1356	5.6%
99	948	3.9%
50	820	3.4%
67	600	2.5%
97	580	2.4%
96	550	2.3%
93	460	1.9%
95	445	1.8%
Other values (90)	8038	33.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_is_superhost
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	34
Missing (%)	0.1%
Memory size	2.9 MiB

0.0	43197
1.0	6902

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	43197	86.2%
1.0	6902	13.8%
(Missing)	34	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	43197	86.2%
1.0	6902	13.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_neighbourhood
Categorical

HIGH CARDINALITY
MISSING

Distinct	235
Distinct (%)	0.6%
Missing	13528
Missing (%)	27.0%
Memory size	3.7 MiB

Montmartre	2233
Le Marais	1921
République	1868
Buttes-Chaumont - Belleville	1803
XI Arrondissement	1733
Other values (230)	27047

Length

Max length	36
Median length	12
Mean length	16.33364294
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	129 ?
Unique (%)	0.4%

Sample

1st row	Saint-Paul - Ile Saint-Louis
2nd row	Le Marais
3rd row	Gare du Nord - Gare de I'Est
4th row	Châtelet - Les Halles - Beaubourg
5th row	République

Common Values

Value	Count	Frequency (%)
Montmartre	2233	4.5%
Le Marais	1921	3.8%
République	1868	3.7%
Buttes-Chaumont - Belleville	1803	3.6%
XI Arrondissement	1733	3.5%
Châtelet - Les Halles - Beaubourg	1503	3.0%
Batignolles	1285	2.6%
Bastille	1280	2.6%
Alésia	1086	2.2%
Saint-Germain-des-Prés - Odéon	1065	2.1%
Other values (225)	20828	41.5%
(Missing)	13528	27.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	12918	14.9%
arrondissement	3678	4.2%
de	3590	4.1%
gare	2321	2.7%
montmartre	2233	2.6%
le	1932	2.2%
marais	1921	2.2%
république	1868	2.2%
belleville	1803	2.1%
buttes-chaumont	1803	2.1%
Other values (321)	52650	60.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_listings_count
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	84
Distinct (%)	0.2%
Missing	34
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	13.0560091

Minimum	0
Maximum	1105
Zeros	8245
Zeros (%)	16.4%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	46
Maximum	1105
Range	1105
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	79.41637975
Coefficient of variation (CV)	6.082745434
Kurtosis	155.8080035
Mean	13.0560091
Median Absolute Deviation (MAD)	0
Skewness	11.92410219
Sum	654093
Variance	6306.961372
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	27341	54.5%
0	8245	16.4%
2	5063	10.1%
3	1595	3.2%
4	995	2.0%
5	723	1.4%
6	453	0.9%
7	412	0.8%
8	295	0.6%
9	254	0.5%
Other values (74)	4723	9.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8245	16.4%
1	27341	54.5%
2	5063	10.1%
3	1595	3.2%
4	995	2.0%
5	723	1.4%
6	453	0.9%
7	412	0.8%
8	295	0.6%
9	254	0.5%

Value	Count	Frequency (%)
1105	209	0.4%
858	36	0.1%
309	13	< 0.1%
273	8	< 0.1%
246	5	< 0.1%
209	173	0.3%
208	1	< 0.1%
192	193	0.4%
188	1	< 0.1%
186	3	< 0.1%

host_total_listings_count
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	84
Distinct (%)	0.2%
Missing	34
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	13.0560091

Minimum	0
Maximum	1105
Zeros	8245
Zeros (%)	16.4%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	46
Maximum	1105
Range	1105
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	79.41637975
Coefficient of variation (CV)	6.082745434
Kurtosis	155.8080035
Mean	13.0560091
Median Absolute Deviation (MAD)	0
Skewness	11.92410219
Sum	654093
Variance	6306.961372
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	27341	54.5%
0	8245	16.4%
2	5063	10.1%
3	1595	3.2%
4	995	2.0%
5	723	1.4%
6	453	0.9%
7	412	0.8%
8	295	0.6%
9	254	0.5%
Other values (74)	4723	9.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8245	16.4%
1	27341	54.5%
2	5063	10.1%
3	1595	3.2%
4	995	2.0%
5	723	1.4%
6	453	0.9%
7	412	0.8%
8	295	0.6%
9	254	0.5%

Value	Count	Frequency (%)
1105	209	0.4%
858	36	0.1%
309	13	< 0.1%
273	8	< 0.1%
246	5	< 0.1%
209	173	0.3%
208	1	< 0.1%
192	193	0.4%
188	1	< 0.1%
186	3	< 0.1%

host_identity_verified
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	34
Missing (%)	0.1%
Memory size	2.9 MiB

1.0	39928
0.0	10171

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	39928	79.6%
0.0	10171	20.3%
(Missing)	34	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	39928	79.7%
0.0	10171	20.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

neighbourhood
Categorical

HIGH CARDINALITY
MISSING

Distinct	220
Distinct (%)	0.7%
Missing	20064
Missing (%)	40.0%
Memory size	4.3 MiB

Paris, Île-de-France, France	27650
Paris, France	655
Paris, IDF, France	304
Paris, Île-de-France Region, France	219
Paris, Ile-de-France, France	62
Other values (215)	1179

Length

Max length	48
Median length	28
Mean length	27.8512754
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	96 ?
Unique (%)	0.3%

Sample

1st row	Paris, Ile-de-France, France
2nd row	Paris, Ile-de-France, France
3rd row	Paris, Ile-de-France, France
4th row	Paris, Ile-de-France, France
5th row	Paris, Île-de-France, France

Common Values

Value	Count	Frequency (%)
Paris, Île-de-France, France	27650	55.2%
Paris, France	655	1.3%
Paris, IDF, France	304	0.6%
Paris, Île-de-France Region, France	219	0.4%
Paris, Ile-de-France, France	62	0.1%
Paris-18E-Arrondissement, Île-de-France, France	42	0.1%
Paris-15E-Arrondissement, Île-de-France, France	39	0.1%
Paris, Paris province, France	36	0.1%
Paris-20E-Arrondissement, Île-de-France, France	35	0.1%
Paris-19E-Arrondissement, Île-de-France, France	31	0.1%
Other values (210)	996	2.0%
(Missing)	20064	40.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
france	30119	33.4%
paris	29502	32.8%
île-de-france	28552	31.7%
idf	313	0.3%
region	221	0.2%
arrondissement	67	0.1%
ile-de-france	63	0.1%
	63	0.1%
paris-18e-arrondissement	42	< 0.1%
paris-15e-arrondissement	39	< 0.1%
Other values (130)	1089	1.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

neighbourhood_cleansed
Categorical

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.1 MiB

Buttes-Montmartre	5355
Popincourt	4590
Vaugirard	3773
Entrepôt	3607
Batignolles-Monceau	3211
Other values (15)	29597

Length

Max length	19
Median length	10
Mean length	10.49685836
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Hôtel-de-Ville
2nd row	Hôtel-de-Ville
3rd row	Opéra
4th row	Louvre
5th row	Popincourt

Common Values

Value	Count	Frequency (%)
Buttes-Montmartre	5355	10.7%
Popincourt	4590	9.2%
Vaugirard	3773	7.5%
Entrepôt	3607	7.2%
Batignolles-Monceau	3211	6.4%
Buttes-Chaumont	2763	5.5%
Ménilmontant	2753	5.5%
Opéra	2582	5.2%
Passy	2509	5.0%
Temple	2330	4.6%
Other values (10)	16660	33.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
buttes-montmartre	5355	10.7%
popincourt	4590	9.2%
vaugirard	3773	7.5%
entrepôt	3607	7.2%
batignolles-monceau	3211	6.4%
buttes-chaumont	2763	5.5%
ménilmontant	2753	5.5%
opéra	2582	5.2%
passy	2509	5.0%
temple	2330	4.6%
Other values (10)	16660	33.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

property_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.3 MiB

House	38721
Apartment	7751
Other	2993
Hotel	668

Length

Max length	9
Median length	5
Mean length	5.618434963
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	House
2nd row	House
3rd row	House
4th row	House
5th row	House

Common Values

Value	Count	Frequency (%)
House	38721	77.2%
Apartment	7751	15.5%
Other	2993	6.0%
Hotel	668	1.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
house	38721	77.2%
apartment	7751	15.5%
other	2993	6.0%
hotel	668	1.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

room_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.9 MiB

Entire home/apt	41329
Private room	7250
Hotel room	1209
Shared room	345

Length

Max length	15
Median length	15
Mean length	14.41804799
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Entire home/apt
2nd row	Entire home/apt
3rd row	Entire home/apt
4th row	Entire home/apt
5th row	Entire home/apt

Common Values

Value	Count	Frequency (%)
Entire home/apt	41329	82.4%
Private room	7250	14.5%
Hotel room	1209	2.4%
Shared room	345	0.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
entire	41329	41.2%
home/apt	41329	41.2%
room	8804	8.8%
private	7250	7.2%
hotel	1209	1.2%
shared	345	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

accommodates
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.05301897

Minimum	0
Maximum	16
Zeros	53
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	2
Q3	4
95-th percentile	6
Maximum	16
Range	16
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.637042015
Coefficient of variation (CV)	0.5362043378
Kurtosis	7.131986549
Mean	3.05301897
Median Absolute Deviation (MAD)	1
Skewness	1.962500007
Sum	153057
Variance	2.679906558
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
2	24428	48.7%
4	12159	24.3%
3	4616	9.2%
6	2854	5.7%
1	2730	5.4%
5	1841	3.7%
8	656	1.3%
7	361	0.7%
10	178	0.4%
12	73	0.1%
Other values (7)	237	0.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	53	0.1%
1	2730	5.4%
2	24428	48.7%
3	4616	9.2%
4	12159	24.3%
5	1841	3.7%
6	2854	5.7%
7	361	0.7%
8	656	1.3%
9	66	0.1%

Value	Count	Frequency (%)
16	27	0.1%
15	27	0.1%
14	22	< 0.1%
13	13	< 0.1%
12	73	0.1%
11	29	0.1%
10	178	0.4%
9	66	0.1%
8	656	1.3%
7	361	0.7%

bathrooms_text
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	31
Distinct (%)	0.1%
Missing	103
Missing (%)	0.2%
Memory size	3.3 MiB

1 bath	37301
1 shared bath	3231
2 baths	2879
1.5 baths	2640
1 private bath	2084
Other values (26)	1895

Length

Max length	17
Median length	6
Mean length	7.153467919
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	1 bath
2nd row	1 bath
3rd row	1 bath
4th row	1 bath
5th row	1 bath

Common Values

Value	Count	Frequency (%)
1 bath	37301	74.4%
1 shared bath	3231	6.4%
2 baths	2879	5.7%
1.5 baths	2640	5.3%
1 private bath	2084	4.2%
2.5 baths	586	1.2%
3 baths	357	0.7%
1.5 shared baths	281	0.6%
Half-bath	199	0.4%
0 baths	79	0.2%
Other values (21)	393	0.8%
(Missing)	103	0.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1	42616	40.4%
bath	42616	40.4%
baths	7163	6.8%
shared	3680	3.5%
2	2955	2.8%
1.5	2921	2.8%
private	2098	2.0%
2.5	600	0.6%
3	360	0.3%
half-bath	251	0.2%
Other values (14)	327	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

bedrooms
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	15
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.303712126

Minimum	1
Maximum	50
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	3
Maximum	50
Range	49
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.9287606415
Coefficient of variation (CV)	0.7123970263
Kurtosis	1200.511608
Mean	1.303712126
Median Absolute Deviation (MAD)	0
Skewness	25.28348159
Sum	65359
Variance	0.8625963292
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
1	39539	78.9%
2	7446	14.9%
3	2361	4.7%
4	610	1.2%
5	129	0.3%
6	26	0.1%
7	7	< 0.1%
50	7	< 0.1%
33	2	< 0.1%
38	1	< 0.1%
Other values (5)	5	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	39539	78.9%
2	7446	14.9%
3	2361	4.7%
4	610	1.2%
5	129	0.3%
6	26	0.1%
7	7	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
23	1	< 0.1%

Value	Count	Frequency (%)
50	7	< 0.1%
38	1	< 0.1%
33	2	< 0.1%
31	1	< 0.1%
29	1	< 0.1%
23	1	< 0.1%
10	1	< 0.1%
8	1	< 0.1%
7	7	< 0.1%
6	26	0.1%

beds
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	23
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.680968623

Minimum	0
Maximum	90
Zeros	1333
Zeros (%)	2.7%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	4
Maximum	90
Range	90
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.377627634
Coefficient of variation (CV)	0.8195439314
Kurtosis	1236.985567
Mean	1.680968623
Median Absolute Deviation (MAD)	0
Skewness	22.19124469
Sum	84272
Variance	1.897857898
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
1	26949	53.8%
2	14201	28.3%
3	4505	9.0%
4	1858	3.7%
0	1333	2.7%
5	721	1.4%
6	307	0.6%
7	107	0.2%
8	78	0.2%
9	38	0.1%
Other values (13)	36	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1333	2.7%
1	26949	53.8%
2	14201	28.3%
3	4505	9.0%
4	1858	3.7%
5	721	1.4%
6	307	0.6%
7	107	0.2%
8	78	0.2%
9	38	0.1%

Value	Count	Frequency (%)
90	1	< 0.1%
85	1	< 0.1%
83	1	< 0.1%
79	1	< 0.1%
77	1	< 0.1%
40	1	< 0.1%
18	2	< 0.1%
16	1	< 0.1%
14	1	< 0.1%
13	2	< 0.1%

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	742
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	120.9666088

Minimum	10
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	10
5-th percentile	36
Q1	60
median	88
Q3	135
95-th percentile	314
Maximum	1000
Range	990
Interquartile range (IQR)	75

Descriptive statistics

Standard deviation	117.671671
Coefficient of variation (CV)	0.9727615923
Kurtosis	21.44778292
Mean	120.9666088
Median Absolute Deviation (MAD)	32
Skewness	3.983086664
Sum	6064419
Variance	13846.62216
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
80	2133	4.3%
60	2066	4.1%
70	2010	4.0%
50	1903	3.8%
100	1804	3.6%
90	1735	3.5%
65	1305	2.6%
75	1273	2.5%
120	1229	2.5%
55	1081	2.2%
Other values (732)	33594	67.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	88	0.2%
11	2	< 0.1%
12	4	< 0.1%
13	3	< 0.1%
14	2	< 0.1%
15	18	< 0.1%
16	6	< 0.1%
17	11	< 0.1%
18	19	< 0.1%
19	16	< 0.1%

Value	Count	Frequency (%)
1000	237	0.5%
999	10	< 0.1%
996	1	< 0.1%
995	1	< 0.1%
992	1	< 0.1%
990	3	< 0.1%
981	1	< 0.1%
978	1	< 0.1%
976	1	< 0.1%
960	1	< 0.1%

minimum_nights
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	84
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	112.9302256

Minimum	1
Maximum	9999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	4
Q3	365
95-th percentile	365
Maximum	9999
Range	9998
Interquartile range (IQR)	363

Descriptive statistics

Standard deviation	170.3706112
Coefficient of variation (CV)	1.508636066
Kurtosis	224.9114029
Mean	112.9302256
Median Absolute Deviation (MAD)	3
Skewness	4.713455745
Sum	5661531
Variance	29026.14518
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
365	14781	29.5%
1	9414	18.8%
2	8547	17.0%
3	6037	12.0%
4	2824	5.6%
30	2550	5.1%
5	2216	4.4%
7	1091	2.2%
6	740	1.5%
10	270	0.5%
Other values (74)	1663	3.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	9414	18.8%
2	8547	17.0%
3	6037	12.0%
4	2824	5.6%
5	2216	4.4%
6	740	1.5%
7	1091	2.2%
8	97	0.2%
9	41	0.1%
10	270	0.5%

Value	Count	Frequency (%)
9999	1	< 0.1%
1124	1	< 0.1%
1120	1	< 0.1%
1112	1	< 0.1%
1100	1	< 0.1%
1001	1	< 0.1%
1000	4	< 0.1%
999	2	< 0.1%
730	1	< 0.1%
523	1	< 0.1%

maximum_nights
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	234
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	999.9625197

Minimum	1
Maximum	10000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	1
5-th percentile	10
Q1	240
median	1125
Q3	1125
95-th percentile	1125
Maximum	10000000
Range	9999999
Interquartile range (IQR)	885

Descriptive statistics

Standard deviation	44664.8205
Coefficient of variation (CV)	44.66649461
Kurtosis	50104.28367
Mean	999.9625197
Median Absolute Deviation (MAD)	0
Skewness	223.8081539
Sum	50131121
Variance	1994946190
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1125	33148	66.1%
365	2561	5.1%
30	2127	4.2%
15	1016	2.0%
7	827	1.6%
60	701	1.4%
10	672	1.3%
90	591	1.2%
1124	548	1.1%
20	534	1.1%
Other values (224)	7408	14.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	57	0.1%
2	115	0.2%
3	193	0.4%
4	198	0.4%
5	317	0.6%
6	342	0.7%
7	827	1.6%
8	240	0.5%
9	81	0.2%
10	672	1.3%

Value	Count	Frequency (%)
10000000	1	< 0.1%
99999	1	< 0.1%
85554	1	< 0.1%
3000	1	< 0.1%
1800	1	< 0.1%
1500	1	< 0.1%
1200	1	< 0.1%
1126	2	< 0.1%
1125	33148	66.1%
1124	548	1.1%

availability_90
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	91
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.03404943

Minimum	0
Maximum	90
Zeros	28647
Zeros (%)	57.1%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	50
95-th percentile	89
Maximum	90
Range	90
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	33.14274539
Coefficient of variation (CV)	1.438858829
Kurtosis	-0.6618748576
Mean	23.03404943
Median Absolute Deviation (MAD)	0
Skewness	1.013857874
Sum	1154766
Variance	1098.441572
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	28647	57.1%
90	1630	3.3%
89	1348	2.7%
88	831	1.7%
1	652	1.3%
87	564	1.1%
83	526	1.0%
70	446	0.9%
9	424	0.8%
39	420	0.8%
Other values (81)	14645	29.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	28647	57.1%
1	652	1.3%
2	399	0.8%
3	305	0.6%
4	267	0.5%
5	234	0.5%
6	208	0.4%
7	220	0.4%
8	219	0.4%
9	424	0.8%

Value	Count	Frequency (%)
90	1630	3.3%
89	1348	2.7%
88	831	1.7%
87	564	1.1%
86	249	0.5%
85	227	0.5%
84	242	0.5%
83	526	1.0%
82	222	0.4%
81	222	0.4%

number_of_reviews
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	440
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	20.83459996

Minimum	0
Maximum	1596
Zeros	11423
Zeros (%)	22.8%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	5
Q3	21
95-th percentile	95
Maximum	1596
Range	1596
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	44.95532338
Coefficient of variation (CV)	2.157724336
Kurtosis	74.57515397
Mean	20.83459996
Median Absolute Deviation (MAD)	5
Skewness	6.026261383
Sum	1044501
Variance	2020.9811
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	11423	22.8%
1	4784	9.5%
2	3214	6.4%
3	2474	4.9%
4	2034	4.1%
5	1749	3.5%
6	1353	2.7%
7	1274	2.5%
8	1165	2.3%
9	1005	2.0%
Other values (430)	19658	39.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11423	22.8%
1	4784	9.5%
2	3214	6.4%
3	2474	4.9%
4	2034	4.1%
5	1749	3.5%
6	1353	2.7%
7	1274	2.5%
8	1165	2.3%
9	1005	2.0%

Value	Count	Frequency (%)
1596	1	< 0.1%
1008	1	< 0.1%
868	1	< 0.1%
796	1	< 0.1%
788	1	< 0.1%
772	1	< 0.1%
758	1	< 0.1%
749	1	< 0.1%
709	1	< 0.1%
664	1	< 0.1%

number_of_reviews_l30d
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	35
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.394111663

Minimum	0
Maximum	208
Zeros	41484
Zeros (%)	82.7%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	208
Range	208
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.593298757
Coefficient of variation (CV)	4.042759722
Kurtosis	5891.650316
Mean	0.394111663
Median Absolute Deviation (MAD)	0
Skewness	50.49864021
Sum	19758
Variance	2.538600929
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
0	41484	82.7%
1	4083	8.1%
2	2053	4.1%
3	1116	2.2%
4	619	1.2%
5	330	0.7%
6	190	0.4%
7	100	0.2%
8	52	0.1%
10	24	< 0.1%
Other values (25)	82	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	41484	82.7%
1	4083	8.1%
2	2053	4.1%
3	1116	2.2%
4	619	1.2%
5	330	0.7%
6	190	0.4%
7	100	0.2%
8	52	0.1%
9	23	< 0.1%

Value	Count	Frequency (%)
208	1	< 0.1%
58	1	< 0.1%
55	1	< 0.1%
51	1	< 0.1%
49	1	< 0.1%
37	1	< 0.1%
36	2	< 0.1%
33	2	< 0.1%
29	3	< 0.1%
27	2	< 0.1%

first_review
Date

MISSING

Distinct	3210
Distinct (%)	8.3%
Missing	11423
Missing (%)	22.8%
Memory size	391.8 KiB

Minimum	2010-02-28 00:00:00
Maximum	2021-09-11 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

review_scores_rating
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

0-79/100	38710
nan	11423

Length

Max length	8
Median length	8
Mean length	6.860730457
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-79/100
2nd row	0-79/100
3rd row	0-79/100
4th row	nan
5th row	0-79/100

Common Values

Value	Count	Frequency (%)
0-79/100	38710	77.2%
nan	11423	22.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-79/100	38710	77.2%
nan	11423	22.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_accuracy
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38023
nan	12110

Length

Max length	6
Median length	6
Mean length	5.275327629
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38023	75.8%
nan	12110	24.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38023	75.8%
nan	12110	24.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_cleanliness
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38028
nan	12105

Length

Max length	6
Median length	6
Mean length	5.275626833
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38028	75.9%
nan	12105	24.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38028	75.9%
nan	12105	24.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_checkin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38010
nan	12123

Length

Max length	6
Median length	6
Mean length	5.274549698
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38010	75.8%
nan	12123	24.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38010	75.8%
nan	12123	24.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_communication
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38021
nan	12112

Length

Max length	6
Median length	6
Mean length	5.275207947
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38021	75.8%
nan	12112	24.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38021	75.8%
nan	12112	24.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_location
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38008
nan	12125

Length

Max length	6
Median length	6
Mean length	5.274430016
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38008	75.8%
nan	12125	24.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38008	75.8%
nan	12125	24.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

review_scores_value
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.5 MiB

0-8/10	38005
nan	12128

Length

Max length	6
Median length	6
Mean length	5.274250494
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0-8/10
2nd row	0-8/10
3rd row	0-8/10
4th row	nan
5th row	0-8/10

Common Values

Value	Count	Frequency (%)
0-8/10	38005	75.8%
nan	12128	24.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0-8/10	38005	75.8%
nan	12128	24.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

instant_bookable
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.8 MiB

0	34160
1	15973

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	34160	68.1%
1	15973	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	34160	68.1%
1	15973	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

calculated_host_listings_count
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	64
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14.6217661

Minimum	1
Maximum	500
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	69
Maximum	500
Range	499
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	58.70327454
Coefficient of variation (CV)	4.014786869
Kurtosis	46.30884423
Mean	14.6217661
Median Absolute Deviation (MAD)	0
Skewness	6.444880195
Sum	733033
Variance	3446.074442
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	35956	71.7%
2	3882	7.7%
3	1134	2.3%
4	820	1.6%
5	730	1.5%
6	528	1.1%
500	500	1.0%
7	441	0.9%
8	384	0.8%
9	279	0.6%
Other values (54)	5479	10.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	35956	71.7%
2	3882	7.7%
3	1134	2.3%
4	820	1.6%
5	730	1.5%
6	528	1.1%
7	441	0.9%
8	384	0.8%
9	279	0.6%
10	270	0.5%

Value	Count	Frequency (%)
500	500	1.0%
250	250	0.5%
209	209	0.4%
193	193	0.4%
184	184	0.4%
173	173	0.3%
133	266	0.5%
103	103	0.2%
94	94	0.2%
93	93	0.2%

calculated_host_listings_count_entire_homes
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	64
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.88757904

Minimum	0
Maximum	500
Zeros	7846
Zeros (%)	15.7%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	69
Maximum	500
Range	500
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	58.67400652
Coefficient of variation (CV)	4.224926918
Kurtosis	46.66464407
Mean	13.88757904
Median Absolute Deviation (MAD)	0
Skewness	6.476993824
Sum	696226
Variance	3442.639041
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	32752	65.3%
0	7846	15.7%
2	2296	4.6%
3	555	1.1%
500	500	1.0%
4	319	0.6%
5	302	0.6%
133	266	0.5%
247	250	0.5%
6	214	0.4%
Other values (54)	4833	9.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	7846	15.7%
1	32752	65.3%
2	2296	4.6%
3	555	1.1%
4	319	0.6%
5	302	0.6%
6	214	0.4%
7	133	0.3%
8	160	0.3%
9	115	0.2%

Value	Count	Frequency (%)
500	500	1.0%
247	250	0.5%
209	209	0.4%
193	193	0.4%
184	184	0.4%
173	173	0.3%
133	266	0.5%
103	103	0.2%
93	187	0.4%
86	86	0.2%

calculated_host_listings_count_private_rooms
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4726427702

Minimum	0
Maximum	31
Zeros	41509
Zeros (%)	82.8%
Negative	0
Negative (%)	0.0%
Memory size	391.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	31
Range	31
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.204134506
Coefficient of variation (CV)	4.663425836
Kurtosis	113.3643454
Mean	0.4726427702
Median Absolute Deviation (MAD)	0
Skewness	9.720016991
Sum	23695
Variance	4.85820892
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
0	41509	82.8%
1	5878	11.7%
2	849	1.7%
4	343	0.7%
3	309	0.6%
6	243	0.5%
5	240	0.5%
7	136	0.3%
9	128	0.3%
8	96	0.2%
Other values (10)	402	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	41509	82.8%
1	5878	11.7%
2	849	1.7%
3	309	0.6%
4	343	0.7%
5	240	0.5%
6	243	0.5%
7	136	0.3%
8	96	0.2%
9	128	0.3%

Value	Count	Frequency (%)
31	63	0.1%
30	60	0.1%
25	44	0.1%
24	24	< 0.1%
23	23	< 0.1%
21	21	< 0.1%
15	30	0.1%
12	24	< 0.1%
11	23	< 0.1%
10	90	0.2%

air_conditioning
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	44175
1.0	5958

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	44175	88.1%
1.0	5958	11.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	44175	88.1%
1.0	5958	11.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

bed_linen
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	29493
1.0	20640

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	29493	58.8%
1.0	20640	41.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	29493	58.8%
1.0	20640	41.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

breakfast
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	44096
1.0	6037

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	44096	88.0%
1.0	6037	12.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	44096	88.0%
1.0	6037	12.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

tv
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

1.0	34180
0.0	15953

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	34180	68.2%
0.0	15953	31.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	34180	68.2%
0.0	15953	31.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

coffee_machine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	28887
1.0	21246

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	28887	57.6%
1.0	21246	42.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	28887	57.6%
1.0	21246	42.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

cooking_basics
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	26472
1.0	23661

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	26472	52.8%
1.0	23661	47.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	26472	52.8%
1.0	23661	47.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

white_goods
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

1.0	38608
0.0	11525

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	38608	77.0%
0.0	11525	23.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	38608	77.0%
0.0	11525	23.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

elevator
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	30888
1.0	19245

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	30888	61.6%
1.0	19245	38.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	30888	61.6%
1.0	19245	38.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

parking
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	36324
1.0	13809

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	36324	72.5%
1.0	13809	27.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	36324	72.5%
1.0	13809	27.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

host_greeting
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	40509
1.0	9624

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	40509	80.8%
1.0	9624	19.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	40509	80.8%
1.0	9624	19.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

internet
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

1.0	47248
0.0	2885

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	47248	94.2%
0.0	2885	5.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	47248	94.2%
0.0	2885	5.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

long_term_stays
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

1.0	43853
0.0	6280

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	43853	87.5%
0.0	6280	12.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	43853	87.5%
0.0	6280	12.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

private_entrance
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.9 MiB

0.0	42413
1.0	7720

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	42413	84.6%
1.0	7720	15.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	42413	84.6%
1.0	7720	15.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

time_since_first_review
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.1 MiB

4+ years	14180
2-3 years	13372
nan	11430
1-2 years	5685
0-6 months	3672

Length

Max length	11
Median length	8
Mean length	7.494005944
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4+ years
2nd row	4+ years
3rd row	4+ years
4th row	nan
5th row	4+ years

Common Values

Value	Count	Frequency (%)
4+ years	14180	28.3%
2-3 years	13372	26.7%
nan	11430	22.8%
1-2 years	5685	11.3%
0-6 months	3672	7.3%
6-12 months	1794	3.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
years	33237	37.4%
4	14180	16.0%
2-3	13372	15.1%
nan	11430	12.9%
1-2	5685	6.4%
months	5466	6.2%
0-6	3672	4.1%
6-12	1794	2.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

time_since_last_review
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.8 MiB

1+ year	28076
nan	11477
2-8 weeks	5410
0-2 weeks	1998
2-6 months	1796

Length

Max length	11
Median length	7
Mean length	6.597071789
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1+ year
2nd row	2-8 weeks
3rd row	1+ year
4th row	nan
5th row	2-6 months

Common Values

Value	Count	Frequency (%)
1+ year	28076	56.0%
nan	11477	22.9%
2-8 weeks	5410	10.8%
0-2 weeks	1998	4.0%
2-6 months	1796	3.6%
6-12 months	1376	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	28076	31.6%
year	28076	31.6%
nan	11477	12.9%
weeks	7408	8.3%
2-8	5410	6.1%
months	3172	3.6%
0-2	1998	2.3%
2-6	1796	2.0%
6-12	1376	1.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id	host_response_time	host_response_rate	host_acceptance_rate	host_is_superhost	host_neighbourhood	host_listings_count	host_total_listings_count	host_identity_verified	neighbourhood	neighbourhood_cleansed	property_type	room_type	accommodates	bathrooms_text	bedrooms	beds	price	minimum_nights	maximum_nights	availability_90	number_of_reviews	number_of_reviews_l30d	first_review	review_scores_rating	review_scores_accuracy	review_scores_cleanliness	review_scores_checkin	review_scores_communication	review_scores_location	review_scores_value	instant_bookable	calculated_host_listings_count	calculated_host_listings_count_entire_homes	calculated_host_listings_count_private_rooms	air_conditioning	bed_linen	tv	coffee_machine	cooking_basics	white_goods	elevator	parking	host_greeting	internet	long_term_stays	time_since_first_review	time_since_last_review
0	5396	within an hour	100%	89%	0.0	Saint-Paul - Ile Saint-Louis	1.0	1.0	1.0	Paris, Ile-de-France, France	Hôtel-de-Ville	House	Entire home/apt	2	1 bath	1.0	1.0	110	2	1125	29	260	3	2013-09-22	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	1	1	0	0.0	1.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	4+ years	1+ year
1	7397	within an hour	100%	80%	1.0	Le Marais	4.0	4.0	1.0	NaN	Hôtel-de-Ville	House	Entire home/apt	4	1 bath	2.0	2.0	100	10	130	20	278	2	2011-08-11	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	1	1	0	0.0	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	1.0	4+ years	2-8 weeks
2	7964	within a day	50-89%	0%	0.0	Gare du Nord - Gare de I'Est	0.0	0.0	1.0	NaN	Opéra	House	Entire home/apt	2	1 bath	1.0	1.0	130	6	365	73	6	0	2014-09-11	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	1	1	0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	4+ years	1+ year
3	9359	within an hour	100%	20%	0.0	Châtelet - Les Halles - Beaubourg	3.0	3.0	1.0	NaN	Louvre	House	Entire home/apt	2	1 bath	1.0	1.0	75	180	365	0	0	0	NaT	nan	nan	nan	nan	nan	nan	nan	0	1	1	0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	1.0	nan	nan
4	9952	within an hour	100%	100%	1.0	République	1.0	1.0	1.0	Paris, Ile-de-France, France	Popincourt	House	Entire home/apt	2	1 bath	1.0	1.0	80	4	31	2	31	1	2016-08-04	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	1	1	0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	1.0	4+ years	2-6 months
5	10586	within a few hours	100%	55%	1.0	Montmartre	4.0	4.0	1.0	Paris, Ile-de-France, France	Buttes-Montmartre	House	Entire home/apt	2	1 bath	1.0	2.0	80	30	300	9	48	0	2011-01-03	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	4	4	0	0.0	0.0	1.0	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	4+ years	1+ year
6	10588	within a few hours	100%	55%	1.0	Montmartre	4.0	4.0	1.0	Paris, Ile-de-France, France	Buttes-Montmartre	House	Entire home/apt	2	1 bath	1.0	1.0	75	30	730	88	18	0	2013-06-03	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	4	4	0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	4+ years	1+ year
7	10917	within an hour	100%	100%	1.0	Ternes	5.0	5.0	1.0	Paris, Île-de-France, France	Batignolles-Monceau	House	Entire home/apt	4	1 bath	1.0	2.0	143	30	279	0	25	0	2010-08-13	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	1	1	1	0	1.0	0.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	4+ years	1+ year
8	11213	within a few hours	100%	71%	0.0	République	2.0	2.0	1.0	Paris, Île-de-France, France	Entrepôt	Apartment	Private room	6	1 private bath	1.0	3.0	170	1	730	0	151	0	2015-10-12	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	2	0	2	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	4+ years	1+ year
9	11265	unknown	unknown	NaN	0.0	Montmartre	1.0	1.0	1.0	Paris, Île-de-France, France	Buttes-Montmartre	House	Entire home/apt	2	1 bath	1.0	1.0	100	7	120	0	16	0	2016-09-09	0-79/100	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0-8/10	0	1	1	0	0.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	1.0	1.0	4+ years	1+ year

Last rows

	id	host_response_time	host_response_rate	host_acceptance_rate	host_is_superhost	host_neighbourhood	host_listings_count	host_total_listings_count	host_identity_verified	neighbourhood	neighbourhood_cleansed	property_type	room_type	accommodates	bathrooms_text	bedrooms	beds	price	minimum_nights	maximum_nights	availability_90	first_review	review_scores_rating	review_scores_accuracy	review_scores_cleanliness	review_scores_checkin	review_scores_communication	review_scores_location	review_scores_value	instant_bookable	calculated_host_listings_count	calculated_host_listings_count_entire_homes	calculated_host_listings_count_private_rooms	air_conditioning	bed_linen	breakfast	tv	coffee_machine	cooking_basics	white_goods	elevator	parking	host_greeting	internet	long_term_stays	private_entrance	time_since_first_review	time_since_last_review
50123	52159765	within an hour	90-99%	95%	0.0	II Arrondissement	85.0	85.0	1.0	Paris, Île-de-France, France	Palais-Bourbon	House	Entire home/apt	2	1 bath	1.0	1.0	102	1	1125	81	NaT	nan	nan	nan	nan	nan	nan	nan	0	69	69	0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	nan	nan
50124	52159958	within an hour	100%	100%	0.0	NaN	0.0	0.0	1.0	NaN	Entrepôt	Hotel	Private room	2	1 private bath	1.0	1.0	112	1	10	77	NaT	nan	nan	nan	nan	nan	nan	nan	1	5	0	5	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	nan	nan
50125	52160741	within an hour	90-99%	98%	0.0	Châtelet - Les Halles - Beaubourg	209.0	209.0	1.0	Paris, Île-de-France, France	Ménilmontant	House	Entire home/apt	4	1 bath	1.0	2.0	89	2	1124	78	NaT	nan	nan	nan	nan	nan	nan	nan	1	173	173	0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	nan	nan
50126	52161033	within an hour	90-99%	98%	0.0	Châtelet - Les Halles - Beaubourg	209.0	209.0	1.0	Paris, Île-de-France, France	Bourse	House	Entire home/apt	2	1 bath	1.0	1.0	1000	2	1125	84	NaT	nan	nan	nan	nan	nan	nan	nan	1	173	173	0	0.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	1.0	0.0	nan	nan
50127	52161127	within an hour	100%	56%	0.0	NaN	0.0	0.0	1.0	NaN	Panthéon	Apartment	Entire home/apt	4	1 bath	1.0	2.0	160	30	1125	84	NaT	nan	nan	nan	nan	nan	nan	nan	1	59	59	0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	1.0	nan	nan
50128	52162381	unknown	unknown	NaN	0.0	Pigalle - Saint-Georges	5.0	5.0	1.0	Paris, Île-de-France, France	Entrepôt	House	Entire home/apt	4	1 bath	1.0	2.0	142	1	1125	86	NaT	nan	nan	nan	nan	nan	nan	nan	1	31	31	0	0.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	nan	nan
50129	52162674	within an hour	50-89%	99%	0.0	NaN	4.0	4.0	1.0	NaN	Passy	Apartment	Entire home/apt	4	1 bath	1.0	2.0	138	1	1125	79	NaT	nan	nan	nan	nan	nan	nan	nan	1	2	2	0	0.0	0.0	0.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	nan	nan
50130	52163316	unknown	unknown	NaN	0.0	Commerce - Dupleix	175.0	175.0	0.0	Paris, Île-de-France, France	Temple	House	Entire home/apt	2	1 bath	1.0	1.0	61	3	1125	81	NaT	nan	nan	nan	nan	nan	nan	nan	1	61	54	4	0.0	0.0	0.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	nan	nan
50131	52165011	within an hour	90-99%	98%	0.0	2nd Arrondissement	138.0	138.0	1.0	Paris, Île-de-France, France	Popincourt	House	Entire home/apt	2	1 bath	1.0	1.0	100	2	1125	85	NaT	nan	nan	nan	nan	nan	nan	nan	1	33	33	0	0.0	1.0	0.0	1.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	nan	nan
50132	52166001	within an hour	100%	100%	1.0	Pigalle - Saint-Georges	1.0	1.0	1.0	NaN	Opéra	House	Entire home/apt	3	1 bath	1.0	3.0	69	30	1125	47	NaT	nan	nan	nan	nan	nan	nan	nan	0	2	2	0	0.0	1.0	0.0	0.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	0.0	nan	nan

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

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Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length