Overview

Dataset statistics

Number of variables20
Number of observations100
Missing cells49
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory165.3 B

Variable types

Text5
Categorical11
Numeric4

Alerts

sun_opn_bsns_time is highly overall correlated with workday_opn_bsns_time and 2 other fieldsHigh correlation
sun_clos_time is highly overall correlated with workday_clos_time and 2 other fieldsHigh correlation
workday_clos_time is highly overall correlated with sat_clos_time and 2 other fieldsHigh correlation
rstde_opn_bsns_time is highly overall correlated with workday_opn_bsns_time and 2 other fieldsHigh correlation
sat_opn_bsns_time is highly overall correlated with workday_opn_bsns_time and 2 other fieldsHigh correlation
sat_clos_time is highly overall correlated with workday_clos_time and 2 other fieldsHigh correlation
rstde_clos_time is highly overall correlated with workday_clos_time and 2 other fieldsHigh correlation
workday_opn_bsns_time is highly overall correlated with sat_opn_bsns_time and 2 other fieldsHigh correlation
zip_no is highly overall correlated with fclty_laHigh correlation
fclty_la is highly overall correlated with zip_noHigh correlation
lclas_nm is highly imbalanced (75.9%)Imbalance
mlsfc_nm is highly imbalanced (62.9%)Imbalance
rstde_guid_cn has 47 (47.0%) missing valuesMissing
esntl_id has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:13:20.444470
Analysis finished2023-12-10 10:13:29.464881
Duration9.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

esntl_id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:29.776698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCCBSPO20N000000001
2nd rowKCCBSPO20N000000812
3rd rowKCCBSPO20N000000003
4th rowKCCBSPO20N000000004
5th rowKCCBSPO20N000000005
ValueCountFrequency (%)
kccbspo20n000000001 1
 
1.0%
kccbspo20n000000063 1
 
1.0%
kccbspo20n000000074 1
 
1.0%
kccbspo20n000000073 1
 
1.0%
kccbspo20n000000072 1
 
1.0%
kccbspo20n000000071 1
 
1.0%
kccbspo20n000000070 1
 
1.0%
kccbspo20n000000069 1
 
1.0%
kccbspo20n000000068 1
 
1.0%
kccbspo20n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:13:30.462088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 814
42.8%
C 200
 
10.5%
2 119
 
6.3%
K 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
S 100
 
5.3%
B 100
 
5.3%
1 24
 
1.3%
Other values (7) 143
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 814
74.0%
2 119
 
10.8%
1 24
 
2.2%
8 22
 
2.0%
4 21
 
1.9%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
C 200
25.0%
K 100
12.5%
O 100
12.5%
N 100
12.5%
P 100
12.5%
S 100
12.5%
B 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 814
74.0%
2 119
 
10.8%
1 24
 
2.2%
8 22
 
2.0%
4 21
 
1.9%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
Latin
ValueCountFrequency (%)
C 200
25.0%
K 100
12.5%
O 100
12.5%
N 100
12.5%
P 100
12.5%
S 100
12.5%
B 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 814
42.8%
C 200
 
10.5%
2 119
 
6.3%
K 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
S 100
 
5.3%
B 100
 
5.3%
1 24
 
1.3%
Other values (7) 143
 
7.5%

fclty_nm
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:30.895887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.13
Min length2

Characters and Unicode

Total characters713
Distinct characters195
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row시아북카페 청라점
2nd row놀숲 아산온양온천점
3rd row밀크북
4th row북카페심심푸리
5th row정글북
ValueCountFrequency (%)
북카페 22
 
15.0%
심심푸리 3
 
2.0%
북카페심심푸리 2
 
1.4%
정글북 2
 
1.4%
북카페세모 2
 
1.4%
시아북카페 2
 
1.4%
북카페마루 1
 
0.7%
청라점 1
 
0.7%
북카페w 1
 
0.7%
엘 1
 
0.7%
Other values (110) 110
74.8%
2023-12-10T19:13:31.616779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
북 86
 
12.1%
카 84
 
11.8%
페 82
 
11.5%
47
 
6.6%
리 19
 
2.7%
심 14
 
2.0%
점 11
 
1.5%
푸 8
 
1.1%
시 8
 
1.1%
이 8
 
1.1%
Other values (185) 346
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 646
90.6%
Space Separator 47
 
6.6%
Decimal Number 10
 
1.4%
Other Punctuation 4
 
0.6%
Lowercase Letter 3
 
0.4%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 86
 
13.3%
카 84
 
13.0%
페 82
 
12.7%
리 19
 
2.9%
심 14
 
2.2%
점 11
 
1.7%
푸 8
 
1.2%
시 8
 
1.2%
이 8
 
1.2%
마 8
 
1.2%
Other values (171) 318
49.2%
Decimal Number
ValueCountFrequency (%)
0 4
40.0%
1 2
20.0%
2 1
 
10.0%
9 1
 
10.0%
5 1
 
10.0%
6 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
33.3%
o 1
33.3%
d 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
R 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
47
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 646
90.6%
Common 61
 
8.6%
Latin 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 86
 
13.3%
카 84
 
13.0%
페 82
 
12.7%
리 19
 
2.9%
심 14
 
2.2%
점 11
 
1.7%
푸 8
 
1.2%
시 8
 
1.2%
이 8
 
1.2%
마 8
 
1.2%
Other values (171) 318
49.2%
Common
ValueCountFrequency (%)
47
77.0%
& 4
 
6.6%
0 4
 
6.6%
1 2
 
3.3%
2 1
 
1.6%
9 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
Latin
ValueCountFrequency (%)
l 1
16.7%
o 1
16.7%
d 1
16.7%
W 1
16.7%
R 1
16.7%
A 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 646
90.6%
ASCII 67
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
북 86
 
13.3%
카 84
 
13.0%
페 82
 
12.7%
리 19
 
2.9%
심 14
 
2.2%
점 11
 
1.7%
푸 8
 
1.2%
시 8
 
1.2%
이 8
 
1.2%
마 8
 
1.2%
Other values (171) 318
49.2%
ASCII
ValueCountFrequency (%)
47
70.1%
& 4
 
6.0%
0 4
 
6.0%
1 2
 
3.0%
l 1
 
1.5%
o 1
 
1.5%
d 1
 
1.5%
W 1
 
1.5%
2 1
 
1.5%
R 1
 
1.5%
Other values (4) 4
 
6.0%

lclas_nm
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
북카페
91 
카페,디저트
 
4
서점
 
2
만화방
 
1
독립서점
 
1

Length

Max length7
Median length3
Mean length3.15
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row북카페
2nd row만화방
3rd row북카페
4th row북카페
5th row북카페

Common Values

ValueCountFrequency (%)
북카페 91
91.0%
카페,디저트 4
 
4.0%
서점 2
 
2.0%
만화방 1
 
1.0%
독립서점 1
 
1.0%
청소년복지시설 1
 
1.0%

Length

2023-12-10T19:13:31.828520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:32.355037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북카페 91
91.0%
카페,디저트 4
 
4.0%
서점 2
 
2.0%
만화방 1
 
1.0%
독립서점 1
 
1.0%
청소년복지시설 1
 
1.0%

mlsfc_nm
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
북카페
84 
만화 카페
14 
영어북카페
 
1
키즈북카페
 
1

Length

Max length5
Median length3
Mean length3.32
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row북카페
2nd row만화 카페
3rd row북카페
4th row만화 카페
5th row북카페

Common Values

ValueCountFrequency (%)
북카페 84
84.0%
만화 카페 14
 
14.0%
영어북카페 1
 
1.0%
키즈북카페 1
 
1.0%

Length

2023-12-10T19:13:32.553668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:32.718796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북카페 84
73.7%
만화 14
 
12.3%
카페 14
 
12.3%
영어북카페 1
 
0.9%
키즈북카페 1
 
0.9%

zip_no
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23280.37
Minimum1834
Maximum63339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:32.905201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1834
5-th percentile3295.1
Q16766.75
median18494.5
Q335048.75
95-th percentile54954.1
Maximum63339
Range61505
Interquartile range (IQR)28282

Descriptive statistics

Standard deviation17819.52
Coefficient of variation (CV)0.76543114
Kurtosis-0.87867599
Mean23280.37
Median Absolute Deviation (MAD)13487.5
Skewness0.60014487
Sum2328037
Variance3.1753529 × 108
MonotonicityNot monotonic
2023-12-10T19:13:33.152932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10881 3
 
3.0%
22003 2
 
2.0%
5017 2
 
2.0%
34394 2
 
2.0%
10859 2
 
2.0%
21927 2
 
2.0%
54542 1
 
1.0%
4735 1
 
1.0%
11735 1
 
1.0%
4178 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
1834 1
1.0%
2741 1
1.0%
2812 1
1.0%
3015 1
1.0%
3145 1
1.0%
3303 1
1.0%
3767 1
1.0%
3785 1
1.0%
3934 1
1.0%
4004 1
1.0%
ValueCountFrequency (%)
63339 1
1.0%
63070 1
1.0%
61487 1
1.0%
58691 1
1.0%
54956 1
1.0%
54954 1
1.0%
54542 1
1.0%
51655 1
1.0%
50937 1
1.0%
49215 1
1.0%

fclty_road_nm_addr
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:33.622286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length25.05
Min length12

Characters and Unicode

Total characters2505
Distinct characters264
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row인천 연수구 아트센터대로 131 커넬워크 여름동 2층 202동218호
2nd row충청남도 아산시 시민로 364-33 지하1층
3rd row경기도 파주시 회동길 121 (문발동)
4th row부산광역시 부산진구 중앙대로702번길 33 (부전동)
5th row광주광역시 동구 백서로125번길 8-1 (금동)
ValueCountFrequency (%)
서울 19
 
3.4%
1층 13
 
2.3%
서울특별시 11
 
2.0%
2층 11
 
2.0%
경기 11
 
2.0%
경기도 10
 
1.8%
동구 7
 
1.2%
3층 6
 
1.1%
마포구 5
 
0.9%
16 5
 
0.9%
Other values (374) 465
82.6%
2023-12-10T19:13:34.352343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
463
 
18.5%
1 116
 
4.6%
로 86
 
3.4%
동 82
 
3.3%
구 72
 
2.9%
시 71
 
2.8%
2 67
 
2.7%
길 52
 
2.1%
서 50
 
2.0%
3 48
 
1.9%
Other values (254) 1398
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1496
59.7%
Space Separator 463
 
18.5%
Decimal Number 424
 
16.9%
Close Punctuation 42
 
1.7%
Open Punctuation 42
 
1.7%
Dash Punctuation 24
 
1.0%
Other Punctuation 6
 
0.2%
Lowercase Letter 5
 
0.2%
Math Symbol 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 86
 
5.7%
동 82
 
5.5%
구 72
 
4.8%
시 71
 
4.7%
길 52
 
3.5%
서 50
 
3.3%
층 42
 
2.8%
울 35
 
2.3%
도 30
 
2.0%
대 30
 
2.0%
Other values (229) 946
63.2%
Decimal Number
ValueCountFrequency (%)
1 116
27.4%
2 67
15.8%
3 48
11.3%
4 36
 
8.5%
7 30
 
7.1%
6 27
 
6.4%
5 27
 
6.4%
9 26
 
6.1%
0 24
 
5.7%
8 23
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
c 1
20.0%
t 1
20.0%
n 1
20.0%
b 1
20.0%
g 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
; 1
 
16.7%
: 1
 
16.7%
/ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
463
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1496
59.7%
Common 1003
40.0%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 86
 
5.7%
동 82
 
5.5%
구 72
 
4.8%
시 71
 
4.7%
길 52
 
3.5%
서 50
 
3.3%
층 42
 
2.8%
울 35
 
2.3%
도 30
 
2.0%
대 30
 
2.0%
Other values (229) 946
63.2%
Common
ValueCountFrequency (%)
463
46.2%
1 116
 
11.6%
2 67
 
6.7%
3 48
 
4.8%
) 42
 
4.2%
( 42
 
4.2%
4 36
 
3.6%
7 30
 
3.0%
6 27
 
2.7%
5 27
 
2.7%
Other values (9) 105
 
10.5%
Latin
ValueCountFrequency (%)
B 1
16.7%
c 1
16.7%
t 1
16.7%
n 1
16.7%
b 1
16.7%
g 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1496
59.7%
ASCII 1009
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
463
45.9%
1 116
 
11.5%
2 67
 
6.6%
3 48
 
4.8%
) 42
 
4.2%
( 42
 
4.2%
4 36
 
3.6%
7 30
 
3.0%
6 27
 
2.7%
5 27
 
2.7%
Other values (15) 111
 
11.0%
Hangul
ValueCountFrequency (%)
로 86
 
5.7%
동 82
 
5.5%
구 72
 
4.8%
시 71
 
4.7%
길 52
 
3.5%
서 50
 
3.3%
층 42
 
2.8%
울 35
 
2.3%
도 30
 
2.0%
대 30
 
2.0%
Other values (229) 946
63.2%

fclty_la
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.844402
Minimum33.492067
Maximum38.108783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:34.635642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.492067
5-th percentile35.112956
Q136.300539
median37.406191
Q337.555636
95-th percentile37.736641
Maximum38.108783
Range4.6167164
Interquartile range (IQR)1.2550964

Descriptive statistics

Standard deviation1.0166815
Coefficient of variation (CV)0.027593921
Kurtosis0.76673521
Mean36.844402
Median Absolute Deviation (MAD)0.26895655
Skewness-1.216411
Sum3684.4402
Variance1.0336413
MonotonicityNot monotonic
2023-12-10T19:13:34.912739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3991127 2
 
2.0%
35.9629708 1
 
1.0%
35.5807562 1
 
1.0%
35.6739596 1
 
1.0%
37.5414894 1
 
1.0%
37.7356712 1
 
1.0%
37.535646 1
 
1.0%
38.108783 1
 
1.0%
37.4862459 1
 
1.0%
37.5736885 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
33.4920666 1
1.0%
33.5454928 1
1.0%
34.802726 1
1.0%
35.0749257 1
1.0%
35.0926907 1
1.0%
35.1140222 1
1.0%
35.135823 1
1.0%
35.1426411 1
1.0%
35.1491874 1
1.0%
35.1555521 1
1.0%
ValueCountFrequency (%)
38.108783 1
1.0%
37.8920821 1
1.0%
37.7882592 1
1.0%
37.7877422 1
1.0%
37.7550745 1
1.0%
37.7356712 1
1.0%
37.728887 1
1.0%
37.7165817 1
1.0%
37.7075393 1
1.0%
37.7074985 1
1.0%

fclty_lo
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.38183
Minimum126.42517
Maximum129.41949
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:35.228873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.42517
5-th percentile126.6371
Q1126.89428
median127.03715
Q3127.43725
95-th percentile129.08292
Maximum129.41949
Range2.9943238
Interquartile range (IQR)0.54297217

Descriptive statistics

Standard deviation0.85483398
Coefficient of variation (CV)0.0067108001
Kurtosis0.176856
Mean127.38183
Median Absolute Deviation (MAD)0.20395195
Skewness1.3033594
Sum12738.183
Variance0.73074113
MonotonicityNot monotonic
2023-12-10T19:13:35.531121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6371187 2
 
2.0%
126.9724793 1
 
1.0%
129.3394032 1
 
1.0%
128.9576198 1
 
1.0%
127.0167959 1
 
1.0%
127.0598759 1
 
1.0%
126.9442422 1
 
1.0%
127.7115643 1
 
1.0%
126.8858454 1
 
1.0%
126.902804 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
126.4251707 1
1.0%
126.4325146 1
1.0%
126.4608802 1
1.0%
126.6082755 1
1.0%
126.6366722 1
1.0%
126.6371187 2
2.0%
126.6768618 1
1.0%
126.6776383 1
1.0%
126.6778011 1
1.0%
126.6871725 1
1.0%
ValueCountFrequency (%)
129.4194945 1
1.0%
129.3436556 1
1.0%
129.3394032 1
1.0%
129.322588 1
1.0%
129.1002664 1
1.0%
129.0820098 1
1.0%
129.0728552 1
1.0%
129.0689117 1
1.0%
129.061119 1
1.0%
129.0442701 1
1.0%

workday_opn_bsns_time
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
10:00
35 
11:00
16 
12:00
11 
9:00
10 
10:30
7 
Other values (11)
21 

Length

Max length30
Median length5
Mean length5.41
Min length4

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row10:00
2nd row13:00
3rd row9:00
4th row10:30
5th row12:00

Common Values

ValueCountFrequency (%)
10:00 35
35.0%
11:00 16
16.0%
12:00 11
 
11.0%
9:00 10
 
10.0%
10:30 7
 
7.0%
9:30 5
 
5.0%
<NA> 5
 
5.0%
13:00 2
 
2.0%
8:30 2
 
2.0%
11:00 (3~9월), 11:00(10~2월) 1
 
1.0%
Other values (6) 6
 
6.0%

Length

2023-12-10T19:13:35.851705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00 36
33.6%
11:00 18
16.8%
12:00 11
 
10.3%
9:00 10
 
9.3%
10:30 7
 
6.5%
9:30 5
 
4.7%
na 5
 
4.7%
13:00 2
 
1.9%
8:30 2
 
1.9%
0:00 1
 
0.9%
Other values (10) 10
 
9.3%

workday_clos_time
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
22:00
17 
21:00
16 
19:00
14 
18:00
13 
23:00
9 
Other values (15)
31 

Length

Max length29
Median length5
Mean length5.59
Min length4

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row19:00
2nd row22:00
3rd row19:00
4th row23:00
5th row21:30

Common Values

ValueCountFrequency (%)
22:00 17
17.0%
21:00 16
16.0%
19:00 14
14.0%
18:00 13
13.0%
23:00 9
9.0%
24:00 7
7.0%
20:00 5
 
5.0%
<NA> 5
 
5.0%
17:00 2
 
2.0%
17:30 2
 
2.0%
Other values (10) 10
10.0%

Length

2023-12-10T19:13:36.075614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22:00 17
15.9%
21:00 16
15.0%
19:00 15
14.0%
18:00 13
12.1%
23:00 9
8.4%
24:00 8
7.5%
20:00 7
6.5%
na 5
 
4.7%
17:00 2
 
1.9%
17:30 2
 
1.9%
Other values (13) 13
12.1%

sat_opn_bsns_time
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
10:00
32 
11:00
20 
<NA>
16 
12:00
9 
9:00
9 
Other values (7)
14 

Length

Max length30
Median length5
Mean length5.17
Min length4

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row10:00
2nd row13:00
3rd row10:00
4th row10:30
5th row12:00

Common Values

ValueCountFrequency (%)
10:00 32
32.0%
11:00 20
20.0%
<NA> 16
16.0%
12:00 9
 
9.0%
9:00 9
 
9.0%
10:30 6
 
6.0%
9:30 3
 
3.0%
13:00 1
 
1.0%
11:00 (3~9월), 11:00(10~2월) 1
 
1.0%
18:00 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T19:13:36.299278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00 33
31.4%
11:00 22
21.0%
na 16
15.2%
12:00 9
 
8.6%
9:00 9
 
8.6%
10:30 6
 
5.7%
9:30 3
 
2.9%
13:00 1
 
1.0%
3~9월 1
 
1.0%
11:00(10~2월 1
 
1.0%
Other values (4) 4
 
3.8%

sat_clos_time
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
22:00
17 
<NA>
16 
18:00
14 
21:00
11 
19:00
10 
Other values (14)
32 

Length

Max length29
Median length5
Mean length5.28
Min length4

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row19:00
2nd row22:00
3rd row20:00
4th row23:00
5th row21:30

Common Values

ValueCountFrequency (%)
22:00 17
17.0%
<NA> 16
16.0%
18:00 14
14.0%
21:00 11
11.0%
19:00 10
10.0%
23:00 8
8.0%
24:00 6
 
6.0%
20:00 6
 
6.0%
17:00 2
 
2.0%
23:30 1
 
1.0%
Other values (9) 9
9.0%

Length

2023-12-10T19:13:36.514535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22:00 17
16.3%
na 16
15.4%
18:00 14
13.5%
21:00 11
10.6%
19:00 10
9.6%
23:00 8
7.7%
24:00 7
6.7%
20:00 7
6.7%
17:00 2
 
1.9%
22:30 1
 
1.0%
Other values (11) 11
10.6%

sun_opn_bsns_time
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
33 
10:00
25 
11:00
14 
12:00
11 
9:00
6 
Other values (8)
11 

Length

Max length30
Median length5
Mean length5.05
Min length4

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row10:00
2nd row13:00
3rd row10:00
4th row10:30
5th row12:00

Common Values

ValueCountFrequency (%)
<NA> 33
33.0%
10:00 25
25.0%
11:00 14
14.0%
12:00 11
 
11.0%
9:00 6
 
6.0%
10:30 4
 
4.0%
13:00 1
 
1.0%
11:00 (3~9월), 11:00(10~2월) 1
 
1.0%
18:00 1
 
1.0%
10:00 (4월~10월), 11:00 (11월~3월) 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T19:13:36.744241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 33
31.4%
10:00 26
24.8%
11:00 16
15.2%
12:00 11
 
10.5%
9:00 6
 
5.7%
10:30 4
 
3.8%
13:00 1
 
1.0%
3~9월 1
 
1.0%
11:00(10~2월 1
 
1.0%
18:00 1
 
1.0%
Other values (5) 5
 
4.8%

sun_clos_time
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
33 
22:00
14 
18:00
9 
21:00
8 
23:00
8 
Other values (13)
28 

Length

Max length29
Median length5
Mean length5.11
Min length4

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row19:00
2nd row22:00
3rd row20:00
4th row23:00
5th row21:30

Common Values

ValueCountFrequency (%)
<NA> 33
33.0%
22:00 14
14.0%
18:00 9
 
9.0%
21:00 8
 
8.0%
23:00 8
 
8.0%
24:00 7
 
7.0%
19:00 6
 
6.0%
20:00 3
 
3.0%
17:00 3
 
3.0%
22:30 1
 
1.0%
Other values (8) 8
 
8.0%

Length

2023-12-10T19:13:36.982547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 33
31.7%
22:00 14
13.5%
18:00 9
 
8.7%
21:00 8
 
7.7%
23:00 8
 
7.7%
24:00 8
 
7.7%
19:00 6
 
5.8%
20:00 4
 
3.8%
17:00 3
 
2.9%
2:00 1
 
1.0%
Other values (10) 10
 
9.6%

rstde_opn_bsns_time
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
64 
10:00
11 
11:00
8 
12:00
 
6
10:30
 
3
Other values (6)
8 

Length

Max length30
Median length4
Mean length4.57
Min length4

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row10:00
2nd row13:00
3rd row10:00
4th row10:30
5th row12:00

Common Values

ValueCountFrequency (%)
<NA> 64
64.0%
10:00 11
 
11.0%
11:00 8
 
8.0%
12:00 6
 
6.0%
10:30 3
 
3.0%
9:00 3
 
3.0%
13:00 1
 
1.0%
18:00 1
 
1.0%
10:00 (4월~10월), 11:00 (11월~3월) 1
 
1.0%
0:00 1
 
1.0%

Length

2023-12-10T19:13:37.191634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 64
62.1%
10:00 12
 
11.7%
11:00 9
 
8.7%
12:00 6
 
5.8%
10:30 3
 
2.9%
9:00 3
 
2.9%
13:00 1
 
1.0%
18:00 1
 
1.0%
4월~10월 1
 
1.0%
11월~3월 1
 
1.0%
Other values (2) 2
 
1.9%

rstde_clos_time
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
64 
23:00
8 
22:00
7 
19:00
 
5
20:00
 
3
Other values (10)
13 

Length

Max length33
Median length4
Mean length4.87
Min length4

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row19:00
2nd row22:00
3rd row20:00
4th row23:00
5th row21:30

Common Values

ValueCountFrequency (%)
<NA> 64
64.0%
23:00 8
 
8.0%
22:00 7
 
7.0%
19:00 5
 
5.0%
20:00 3
 
3.0%
24:00 3
 
3.0%
18:00 2
 
2.0%
21:30 1
 
1.0%
2:00 1
 
1.0%
22:30 1
 
1.0%
Other values (5) 5
 
5.0%

Length

2023-12-10T19:13:37.492918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 64
61.0%
23:00 8
 
7.6%
22:00 7
 
6.7%
19:00 5
 
4.8%
24:00 5
 
4.8%
20:00 3
 
2.9%
18:00 2
 
1.9%
02:00 1
 
1.0%
23:00(11월~3월 1
 
1.0%
4월~10월 1
 
1.0%
Other values (8) 8
 
7.6%

rstde_guid_cn
Text

MISSING 

Distinct29
Distinct (%)54.7%
Missing47
Missing (%)47.0%
Memory size932.0 B
2023-12-10T19:13:37.850930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length23
Mean length10.245283
Min length5

Characters and Unicode

Total characters543
Distinct characters71
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)41.5%

Sample

1st row매주 월요일 휴무, 13~14시 브레이크타임
2nd row설날, 추석 당일 휴무
3rd row매주 월요일 휴무
4th row연중 무휴
5th row월요일 휴무
ValueCountFrequency (%)
휴무 54
33.3%
일요일 16
 
9.9%
월요일 14
 
8.6%
공휴일 10
 
6.2%
주말 9
 
5.6%
연중 4
 
2.5%
무휴 4
 
2.5%
매주 4
 
2.5%
추석 3
 
1.9%
당일 3
 
1.9%
Other values (35) 41
25.3%
2023-12-10T19:13:38.439927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
20.1%
휴 74
13.6%
일 72
13.3%
무 59
10.9%
요 35
 
6.4%
, 20
 
3.7%
공 18
 
3.3%
월 15
 
2.8%
주 14
 
2.6%
0 10
 
1.8%
Other values (61) 117
21.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 386
71.1%
Space Separator 109
 
20.1%
Other Punctuation 25
 
4.6%
Decimal Number 20
 
3.7%
Dash Punctuation 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
휴 74
19.2%
일 72
18.7%
무 59
15.3%
요 35
9.1%
공 18
 
4.7%
월 15
 
3.9%
주 14
 
3.6%
말 9
 
2.3%
매 4
 
1.0%
지 4
 
1.0%
Other values (51) 82
21.2%
Decimal Number
ValueCountFrequency (%)
0 10
50.0%
1 4
 
20.0%
3 2
 
10.0%
4 2
 
10.0%
2 2
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 20
80.0%
: 5
 
20.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 386
71.1%
Common 157
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
휴 74
19.2%
일 72
18.7%
무 59
15.3%
요 35
9.1%
공 18
 
4.7%
월 15
 
3.9%
주 14
 
3.6%
말 9
 
2.3%
매 4
 
1.0%
지 4
 
1.0%
Other values (51) 82
21.2%
Common
ValueCountFrequency (%)
109
69.4%
, 20
 
12.7%
0 10
 
6.4%
: 5
 
3.2%
1 4
 
2.5%
3 2
 
1.3%
4 2
 
1.3%
2 2
 
1.3%
- 2
 
1.3%
~ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 386
71.1%
ASCII 157
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
69.4%
, 20
 
12.7%
0 10
 
6.4%
: 5
 
3.2%
1 4
 
2.5%
3 2
 
1.3%
4 2
 
1.3%
2 2
 
1.3%
- 2
 
1.3%
~ 1
 
0.6%
Hangul
ValueCountFrequency (%)
휴 74
19.2%
일 72
18.7%
무 59
15.3%
요 35
9.1%
공 18
 
4.7%
월 15
 
3.9%
주 14
 
3.6%
말 9
 
2.3%
매 4
 
1.0%
지 4
 
1.0%
Other values (51) 82
21.2%

tel_no
Real number (ℝ)

Distinct98
Distinct (%)99.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean1.7572775 × 1010
Minimum23569410
Maximum5.0714964 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:38.675130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23569410
5-th percentile2.0122662 × 108
Q13.2259532 × 108
median1.0328479 × 109
Q35.0713283 × 1010
95-th percentile5.0714197 × 1010
Maximum5.0714964 × 1010
Range5.0691395 × 1010
Interquartile range (IQR)5.0390688 × 1010

Descriptive statistics

Standard deviation2.3591453 × 1010
Coefficient of variation (CV)1.3425001
Kurtosis-1.51778
Mean1.7572775 × 1010
Median Absolute Deviation (MAD)8.0068442 × 108
Skewness0.70676826
Sum1.7397047 × 1012
Variance5.5655665 × 1020
MonotonicityNot monotonic
2023-12-10T19:13:38.919605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50713282878 2
 
2.0%
1094664888 1
 
1.0%
50714964100 1
 
1.0%
1084161701 1
 
1.0%
7042227712 1
 
1.0%
50713410325 1
 
1.0%
1034701305 1
 
1.0%
50714233133 1
 
1.0%
1037280705 1
 
1.0%
25810335 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
23569410 1
1.0%
24006802 1
1.0%
24632008 1
1.0%
25810335 1
1.0%
28827522 1
1.0%
220382070 1
1.0%
220512727 1
1.0%
221550078 1
1.0%
222786607 1
1.0%
222867351 1
1.0%
ValueCountFrequency (%)
50714964100 1
1.0%
50714471315 1
1.0%
50714310087 1
1.0%
50714266040 1
1.0%
50714233133 1
1.0%
50714192570 1
1.0%
50714183351 1
1.0%
50714170603 1
1.0%
50714150154 1
1.0%
50714087111 1
1.0%

optn_dc
Text

Distinct96
Distinct (%)97.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T19:13:39.352209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length48
Mean length34.525253
Min length4

Characters and Unicode

Total characters3418
Distinct characters384
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.9%

Sample

1st row아동 그림책 독후 활동, 책을 읽어주는 선생님이 상주, 36개월 이상 어린이만 시설 이용 가능, 예약을 통해 이용 가능
2nd row어린이 책방, 음악을 들으면서 독서활동
3rd row만화카페, 차별화된 인테리어, 음식주문 가능
4th row독서 활동 장소, 공부하기 좋은 분위기
5th row만화카페, 편한 소파베드, 3만여권의 만화책
ValueCountFrequency (%)
가능 28
 
3.2%
수 20
 
2.3%
있는 18
 
2.1%
카페 14
 
1.6%
책 14
 
1.6%
좋은 14
 
1.6%
북카페 14
 
1.6%
분위기 13
 
1.5%
만화카페 12
 
1.4%
장소 11
 
1.3%
Other values (515) 714
81.9%
2023-12-10T19:13:40.058067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
773
 
22.6%
, 141
 
4.1%
가 55
 
1.6%
한 55
 
1.6%
서 54
 
1.6%
페 50
 
1.5%
카 48
 
1.4%
기 43
 
1.3%
는 40
 
1.2%
이 39
 
1.1%
Other values (374) 2120
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2435
71.2%
Space Separator 773
 
22.6%
Other Punctuation 144
 
4.2%
Decimal Number 52
 
1.5%
Lowercase Letter 13
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 55
 
2.3%
한 55
 
2.3%
서 54
 
2.2%
페 50
 
2.1%
카 48
 
2.0%
기 43
 
1.8%
는 40
 
1.6%
이 39
 
1.6%
하 38
 
1.6%
책 37
 
1.5%
Other values (354) 1976
81.1%
Lowercase Letter
ValueCountFrequency (%)
t 2
15.4%
e 2
15.4%
i 2
15.4%
a 2
15.4%
r 2
15.4%
c 1
7.7%
v 1
7.7%
n 1
7.7%
Decimal Number
ValueCountFrequency (%)
0 21
40.4%
2 10
19.2%
1 6
 
11.5%
3 6
 
11.5%
5 5
 
9.6%
6 3
 
5.8%
4 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 141
97.9%
' 2
 
1.4%
" 1
 
0.7%
Space Separator
ValueCountFrequency (%)
773
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2435
71.2%
Common 969
 
28.3%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 55
 
2.3%
한 55
 
2.3%
서 54
 
2.2%
페 50
 
2.1%
카 48
 
2.0%
기 43
 
1.8%
는 40
 
1.6%
이 39
 
1.6%
하 38
 
1.6%
책 37
 
1.5%
Other values (354) 1976
81.1%
Common
ValueCountFrequency (%)
773
79.8%
, 141
 
14.6%
0 21
 
2.2%
2 10
 
1.0%
1 6
 
0.6%
3 6
 
0.6%
5 5
 
0.5%
6 3
 
0.3%
' 2
 
0.2%
" 1
 
0.1%
Latin
ValueCountFrequency (%)
t 2
14.3%
e 2
14.3%
i 2
14.3%
a 2
14.3%
r 2
14.3%
c 1
7.1%
v 1
7.1%
n 1
7.1%
B 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2435
71.2%
ASCII 983
28.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
773
78.6%
, 141
 
14.3%
0 21
 
2.1%
2 10
 
1.0%
1 6
 
0.6%
3 6
 
0.6%
5 5
 
0.5%
6 3
 
0.3%
' 2
 
0.2%
t 2
 
0.2%
Other values (10) 14
 
1.4%
Hangul
ValueCountFrequency (%)
가 55
 
2.3%
한 55
 
2.3%
서 54
 
2.2%
페 50
 
2.1%
카 48
 
2.0%
기 43
 
1.8%
는 40
 
1.6%
이 39
 
1.6%
하 38
 
1.6%
책 37
 
1.5%
Other values (354) 1976
81.1%

adit_dc
Categorical

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
리뷰여부 : 있음
16 
주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
 
6
주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음
 
6
화장실 남녀구분 : 구분, 무선 인터넷 : 가능, 리뷰여부 : 있음
 
5
주차 : 가능, 리뷰여부 : 있음
 
5
Other values (43)
62 

Length

Max length84
Median length66
Mean length44.34
Min length9

Unique

Unique33 ?
Unique (%)33.0%

Sample

1st row주차 : 가능, 화장실 남녀구분 : 구분, 북토크 : 가능, 예약 : 가능, 무선 인터넷 : 가능, 유아시설 : 가능, 리뷰여부 : 있음
2nd row화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
3rd row주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음
4th row화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
5th row리뷰여부 : 있음

Common Values

ValueCountFrequency (%)
리뷰여부 : 있음 16
 
16.0%
주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음 6
 
6.0%
주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음 6
 
6.0%
화장실 남녀구분 : 구분, 무선 인터넷 : 가능, 리뷰여부 : 있음 5
 
5.0%
주차 : 가능, 리뷰여부 : 있음 5
 
5.0%
주차 : 가능, 화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음 4
 
4.0%
화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음 4
 
4.0%
주차 : 가능, 화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음 4
 
4.0%
주차 : 가능, 화장실 남녀구분 : 구분, 무선 인터넷 : 가능, 리뷰여부 : 있음 3
 
3.0%
화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음 3
 
3.0%
Other values (38) 44
44.0%

Length

2023-12-10T19:13:40.324511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
413
30.2%
가능 262
19.2%
리뷰여부 92
 
6.7%
있음 92
 
6.7%
무선 69
 
5.0%
인터넷 69
 
5.0%
화장실 59
 
4.3%
남녀구분 59
 
4.3%
구분 59
 
4.3%
단체석 56
 
4.1%
Other values (6) 137
 
10.0%

Interactions

2023-12-10T19:13:27.253034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:24.838485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.532133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:26.310177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:27.457920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.000236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.733967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:26.535613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:27.635208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.180222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.897559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:26.774786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:27.834890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:25.370312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:26.123783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:27.032571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:13:40.519111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
esntl_idfclty_nmlclas_nmmlsfc_nmzip_nofclty_road_nm_addrfclty_lafclty_loworkday_opn_bsns_timeworkday_clos_timesat_opn_bsns_timesat_clos_timesun_opn_bsns_timesun_clos_timerstde_opn_bsns_timerstde_clos_timerstde_guid_cntel_nooptn_dcadit_dc
esntl_id1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
fclty_nm1.0001.0001.0001.0001.0000.9990.8240.9740.0000.0001.0001.0001.0001.0001.0001.0001.0000.8650.9990.964
lclas_nm1.0001.0001.0000.0000.2501.0000.2560.0000.6460.0000.6270.0000.6330.0000.6900.0000.6590.0811.0000.407
mlsfc_nm1.0001.0000.0001.0000.2131.0000.1160.0000.0000.3380.0000.7150.1630.7050.6810.5950.7520.0001.0000.846
zip_no1.0001.0000.2500.2131.0001.0000.8890.7820.5870.5940.3720.6540.6150.6560.4550.6790.5490.2850.9510.000
fclty_road_nm_addr1.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9801.0001.0001.000
fclty_la1.0000.8240.2560.1160.8891.0001.0000.8720.4930.3380.3430.2400.6240.0000.4720.0000.0000.4270.9240.000
fclty_lo1.0000.9740.0000.0000.7821.0000.8721.0000.3900.5620.4620.6200.5890.5390.5590.4260.0000.3200.9850.000
workday_opn_bsns_time1.0000.0000.6460.0000.5871.0000.4930.3901.0000.8610.9740.7710.9950.8380.9990.3120.0000.0001.0000.817
workday_clos_time1.0000.0000.0000.3380.5941.0000.3380.5620.8611.0000.7650.9920.7530.9860.6510.9770.7080.0670.9980.693
sat_opn_bsns_time1.0001.0000.6270.0000.3721.0000.3430.4620.9740.7651.0000.7470.9890.7510.9850.5020.0000.0001.0000.000
sat_clos_time1.0001.0000.0000.7150.6541.0000.2400.6200.7710.9920.7471.0000.7100.9990.5560.9990.4090.0000.9970.000
sun_opn_bsns_time1.0001.0000.6330.1630.6151.0000.6240.5890.9950.7530.9890.7101.0000.8170.9840.3880.0000.0001.0000.777
sun_clos_time1.0001.0000.0000.7050.6561.0000.0000.5390.8380.9860.7510.9990.8171.0000.5360.9880.0000.0000.9950.000
rstde_opn_bsns_time1.0001.0000.6900.6810.4551.0000.4720.5590.9990.6510.9850.5560.9840.5361.0000.4360.0000.0001.0000.364
rstde_clos_time1.0001.0000.0000.5950.6791.0000.0000.4260.3120.9770.5020.9990.3880.9880.4361.0000.7050.0001.0000.000
rstde_guid_cn1.0001.0000.6590.7520.5490.9800.0000.0000.0000.7080.0000.4090.0000.0000.0000.7051.0000.0000.9800.802
tel_no1.0000.8650.0810.0000.2851.0000.4270.3200.0000.0670.0000.0000.0000.0000.0000.0000.0001.0000.9410.714
optn_dc1.0000.9991.0001.0000.9511.0000.9240.9851.0000.9981.0000.9971.0000.9951.0001.0000.9800.9411.0000.999
adit_dc1.0000.9640.4070.8460.0001.0000.0000.0000.8170.6930.0000.0000.7770.0000.3640.0000.8020.7140.9991.000
2023-12-10T19:13:40.815272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
sun_opn_bsns_timelclas_nmsun_clos_timeworkday_clos_timerstde_opn_bsns_timesat_opn_bsns_timesat_clos_timeadit_dcrstde_clos_timemlsfc_nmworkday_opn_bsns_time
sun_opn_bsns_time1.0000.3880.4420.3920.9260.9360.3260.2800.0980.0460.863
lclas_nm0.3881.0000.0000.0000.4360.3700.0000.1110.0000.0000.347
sun_clos_time0.4420.0001.0000.8830.2080.3710.9300.0000.9020.4490.471
workday_clos_time0.3920.0000.8831.0000.3000.4100.9080.1730.8450.1690.478
rstde_opn_bsns_time0.9260.4360.2080.3001.0000.9310.2130.0000.1340.4590.931
sat_opn_bsns_time0.9360.3700.3710.4100.9311.0000.3680.0000.1830.0000.871
sat_clos_time0.3260.0000.9300.9080.2130.3681.0000.0000.9350.4340.363
adit_dc0.2800.1110.0000.1730.0000.0000.0001.0000.0000.4170.281
rstde_clos_time0.0980.0000.9020.8450.1340.1830.9350.0001.0000.3670.030
mlsfc_nm0.0460.0000.4490.1690.4590.0000.4340.4170.3671.0000.000
workday_opn_bsns_time0.8630.3470.4710.4780.9310.8710.3630.2810.0300.0001.000
2023-12-10T19:13:41.054978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
zip_nofclty_lafclty_lotel_nolclas_nmmlsfc_nmworkday_opn_bsns_timeworkday_clos_timesat_opn_bsns_timesat_clos_timesun_opn_bsns_timesun_clos_timerstde_opn_bsns_timerstde_clos_timeadit_dc
zip_no1.000-0.8360.3360.1950.1280.0770.2530.2490.1660.2950.3110.2970.1460.3150.000
fclty_la-0.8361.000-0.386-0.2360.1250.0670.2230.1310.1610.0810.3060.0000.2310.0000.000
fclty_lo0.336-0.3861.0000.1090.0000.0000.1660.2530.2310.2920.2810.2310.2950.1010.000
tel_no0.195-0.2360.1091.0000.0310.0000.0000.0580.0000.0000.0000.0000.0000.0000.339
lclas_nm0.1280.1250.0000.0311.0000.0000.3470.0000.3700.0000.3880.0000.4360.0000.111
mlsfc_nm0.0770.0670.0000.0000.0001.0000.0000.1690.0000.4340.0460.4490.4590.3670.417
workday_opn_bsns_time0.2530.2230.1660.0000.3470.0001.0000.4780.8710.3630.8630.4710.9310.0300.281
workday_clos_time0.2490.1310.2530.0580.0000.1690.4781.0000.4100.9080.3920.8830.3000.8450.173
sat_opn_bsns_time0.1660.1610.2310.0000.3700.0000.8710.4101.0000.3680.9360.3710.9310.1830.000
sat_clos_time0.2950.0810.2920.0000.0000.4340.3630.9080.3681.0000.3260.9300.2130.9350.000
sun_opn_bsns_time0.3110.3060.2810.0000.3880.0460.8630.3920.9360.3261.0000.4420.9260.0980.280
sun_clos_time0.2970.0000.2310.0000.0000.4490.4710.8830.3710.9300.4421.0000.2080.9020.000
rstde_opn_bsns_time0.1460.2310.2950.0000.4360.4590.9310.3000.9310.2130.9260.2081.0000.1340.000
rstde_clos_time0.3150.0000.1010.0000.0000.3670.0300.8450.1830.9350.0980.9020.1341.0000.000
adit_dc0.0000.0000.0000.3390.1110.4170.2810.1730.0000.0000.2800.0000.0000.0001.000

Missing values

2023-12-10T19:13:28.127342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:13:28.746464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-10T19:13:29.160833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

esntl_idfclty_nmlclas_nmmlsfc_nmzip_nofclty_road_nm_addrfclty_lafclty_loworkday_opn_bsns_timeworkday_clos_timesat_opn_bsns_timesat_clos_timesun_opn_bsns_timesun_clos_timerstde_opn_bsns_timerstde_clos_timerstde_guid_cntel_nooptn_dcadit_dc
0KCCBSPO20N000000001시아북카페 청라점북카페북카페22003인천 연수구 아트센터대로 131 커넬워크 여름동 2층 202동218호37.399113126.63711910:0019:0010:0019:0010:0019:0010:0019:00매주 월요일 휴무, 13~14시 브레이크타임50713282878아동 그림책 독후 활동, 책을 읽어주는 선생님이 상주, 36개월 이상 어린이만 시설 이용 가능, 예약을 통해 이용 가능주차 : 가능, 화장실 남녀구분 : 구분, 북토크 : 가능, 예약 : 가능, 무선 인터넷 : 가능, 유아시설 : 가능, 리뷰여부 : 있음
1KCCBSPO20N000000812놀숲 아산온양온천점만화방만화 카페31513충청남도 아산시 시민로 364-33 지하1층36.781113127.00334513:0022:0013:0022:0013:0022:0013:0022:00<NA>415459870<NA>화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
2KCCBSPO20N000000003밀크북북카페북카페10881경기도 파주시 회동길 121 (문발동)37.707498126.6875599:0019:0010:0020:0010:0020:0010:0020:00설날, 추석 당일 휴무319443966어린이 책방, 음악을 들으면서 독서활동주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음
3KCCBSPO20N000000004북카페심심푸리북카페만화 카페47292부산광역시 부산진구 중앙대로702번길 33 (부전동)35.155552129.06111910:3023:0010:3023:0010:3023:0010:3023:00<NA>518031088만화카페, 차별화된 인테리어, 음식주문 가능화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
4KCCBSPO20N000000005정글북북카페북카페61487광주광역시 동구 백서로125번길 8-1 (금동)35.142641126.91915812:0021:3012:0021:3012:0021:3012:0021:30매주 월요일 휴무622347279독서 활동 장소, 공부하기 좋은 분위기리뷰여부 : 있음
5KCCBSPO20N000000006카툰앤북카페 검정고무신 건대입구점북카페만화 카페5017서울 광진구 아차산로 241 연한빌딩 3층37.540498127.07012810:002:0010:002:0010:002:0010:002:00연중 무휴24632008만화카페, 편한 소파베드, 3만여권의 만화책화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음
6KCCBSPO20N000000007청동북카페북카페북카페54956전북 전주시 완산구 세내로 504-7 1층35.832578127.10379310:0021:0012:0018:0012:0018:0012:0018:00<NA>50714310087독서 활동 장소, 많은 종류의 책과 음식리뷰여부 : 있음
7KCCBSPO20N000000813책방 세간독립서점북카페33124충청남도 부여군 규암면 자온로 82 책방 세:간36.273751126.88880812:0019:0012:0019:0012:0019:0012:0019:00<NA>418348205독립서점, 북카페화장실 남녀구분 : 구분, 무선 인터넷 : 가능, 리뷰여부 : 있음
8KCCBSPO20N000000009미스터힐링 양정점북카페만화 카페47210부산 부산진구 중앙대로969번길 11 롯데갤러리움상가 1층 c동 101호35.175874129.07285510:0023:009:0024:009:0024:00<NA><NA><NA>518529589소통 카페, 만화카페, 세미나실이 있어 모임하기에 적합한 장소, 롯데갤러리움 지하주차장 이용시 3시간 무료주차주차 : 가능, 화장실 남녀구분 : 구분, 공간대여 : 가능, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
9KCCBSPO20N000000010시아북카페 송도점북카페북카페22003인천 연수구 아트센터대로 131 커넬워크 여름동 2층 202동218호37.399113126.63711910:0019:0010:0019:0010:0019:00<NA><NA>월요일 휴무50713282878아동 그림책 독후 활동, 책을 읽어주는 선생님이 상주, 36개월 이상 어린이만 시설 이용 가능, 예약을 통해 이용 가능주차 : 가능, 화장실 남녀구분 : 구분, 북토크 : 가능, 예약 : 가능, 무선 인터넷 : 가능, 유아시설 : 가능, 리뷰여부 : 있음
esntl_idfclty_nmlclas_nmmlsfc_nmzip_nofclty_road_nm_addrfclty_lafclty_loworkday_opn_bsns_timeworkday_clos_timesat_opn_bsns_timesat_clos_timesun_opn_bsns_timesun_clos_timerstde_opn_bsns_timerstde_clos_timerstde_guid_cntel_nooptn_dcadit_dc
90KCCBSPO20N000000091쑬딴스북카페북카페북카페10859경기 파주시 탄현면 헤이리마을길 21-7 더 장미건물 1층37.788259126.69611110:0021:00<NA><NA><NA><NA><NA><NA><NA>1032124027전공 공예 작품, 도자기 공방, 물레 체험, 신진 작가들의 작품 전시 갤러리 등 다양한 체험 가능주차 : 가능, 화장실 남녀구분 : 구분, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
91KCCBSPO20N000000092초록우산북카페북카페북카페44078울산광역시 동구 월봉10길 14 (화정동)35.494622129.41949510:0017:0010:0016:00<NA><NA><NA><NA>일요일, 공휴일 휴무522363139울산 동구 무료 도서 대여, 수익금은 전액 복지사업 기금으로 사용리뷰여부 : 있음
92KCCBSPO20N000000093북카페북카페북카페33115충남 부여군 규암면 백제문로 367 한국전통문화대학교 학술정보관 2층36.309469126.89688808:30 (학기중), 09:00(방학중)20:00 (학기중), 19:00 (방학중)<NA><NA><NA><NA><NA><NA><NA>418307181커피와 간단한 문구류 구입 가능화장실 남녀구분 : 구분, 단체석 : 가능, 포장 : 가능, 리뷰여부 : 있음
93KCCBSPO20N000000094바오밥 북카페북카페북카페21104인천광역시 계양구 새풀로 30 (효성동)37.526218126.69921510:0018:0010:0018:0010:0018:00<NA><NA><NA>1043646430비영리 북카페로 편한 마음으로 책 읽고 마을 주민들과 소통 할 수 있는 카페리뷰여부 : 있음
94KCCBSPO20N000000095더플레이그라운드불&베이커리카페,디저트북카페41074대구광역시 동구 신서로 77 (신서동)35.875057128.7237239:0022:009:0022:009:0022:00<NA><NA><NA>7075804772매일 아침 갓 구운 빵과 직접 로스팅하는 원두로 커피를 제조주차 : 가능, 리뷰여부 : 있음
95KCCBSPO20N000000096북카페세모카페,디저트북카페5017서울 광진구 아차산로31길 20 2층, 3층37.5419127.06973812:0024:0011:0024:0011:0024:0012:0024:00<NA>50713698005책, 디저트, 와인과 함께 파티가 열리는 곳, 신간 베스트셀러 200여권의 책 비치, 직접 로스팅한 원두 사용주차 : 가능, 화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음
96KCCBSPO20N000000097당인리책발전소서점북카페4004서울특별시 마포구 월드컵로14길 10-8 (서교동)37.555682126.91112610:0022:0010:0022:0010:0022:00<NA><NA><NA><NA>카페와 독립서점을 한 공간에서 즐길 수 있는 장소, 오상진 김소영 아나운서가 운영하는 북카페리뷰여부 : 있음
97KCCBSPO20N000000098노마드북카페북카페북카페14037경기도 안양시 만안구 태평로60번길 42 (안양동)37.396393126.9307269:0021:009:0021:00<NA><NA><NA><NA>일요일 휴무50713040393깜끔하고 맛있는 음식, 택배 가능주차 : 가능, 화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
98KCCBSPO20N000000099북카페세모 중리점카페,디저트북카페34394대전 대덕구 한밭대로 1097 1층36.359118127.42065712:0023:50<NA><NA><NA><NA><NA><NA><NA>50713338054매장에서 직접 만든 신선한 디저트와 베이커리, 직접로스팅한 커피, 트렌디한 인테리어, 자리마다 콘센트 구비, 200원의 베스트셀러 책 구비주차 : 가능, 화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 리뷰여부 : 있음
99KCCBSPO20N000000100북카페파오카페,디저트북카페3767서울 서대문구 이화여대길 34 신흥빌딩 3층37.558439126.94592412:0022:0011:0022:0011:0022:00<NA><NA><NA>50714041130기획, 전시, 강의, 독립출판을 겸하고 있으며 북마페와 서점을 갖춘 복합 문화 공간, 매달 다양한 문화 행사 진행화장실 남녀구분 : 구분, 예약 : 가능, 단체석 : 가능, 무선 인터넷 : 가능, 포장 : 가능, 리뷰여부 : 있음