Overview

Dataset statistics

Number of variables20
Number of observations2003
Missing cells2925
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory313.1 KiB
Average record size in memory160.1 B

Variable types

Text5
Categorical5
Unsupported10

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21705/F/1/datasetView.do

Alerts

Unnamed: 2 is highly overall correlated with Unnamed: 3 and 3 other fieldsHigh correlation
Unnamed: 3 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 18 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 19 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 17 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 3 is highly imbalanced (56.3%)Imbalance
Unnamed: 17 is highly imbalanced (99.1%)Imbalance
Unnamed: 18 is highly imbalanced (99.1%)Imbalance
Unnamed: 19 is highly imbalanced (56.2%)Imbalance
Unnamed: 8 has 523 (26.1%) missing valuesMissing
Unnamed: 9 has 35 (1.7%) missing valuesMissing
Unnamed: 10 has 25 (1.2%) missing valuesMissing
Unnamed: 11 has 145 (7.2%) missing valuesMissing
Unnamed: 12 has 109 (5.4%) missing valuesMissing
Unnamed: 14 has 58 (2.9%) missing valuesMissing
Unnamed: 16 has 2001 (99.9%) missing valuesMissing
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 09:16:14.955854
Analysis finished2023-12-11 09:16:16.341980
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동인구_관찰조사_2013
Text

Distinct2002
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:16:16.747738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length3.454046
Min length1

Characters and Unicode

Total characters6915
Distinct characters27
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2002 ?
Unique (%)100.0%

Sample

1st rowID관찰조사
2nd rowID_OBSERV_EXAMIN
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
13 1
 
< 0.1%
1328 1
 
< 0.1%
1342 1
 
< 0.1%
1341 1
 
< 0.1%
1340 1
 
< 0.1%
1339 1
 
< 0.1%
1338 1
 
< 0.1%
1337 1
 
< 0.1%
1336 1
 
< 0.1%
1335 1
 
< 0.1%
Other values (1992) 1992
99.5%
2023-12-11T18:16:17.390941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1600
23.1%
2 601
 
8.7%
5 600
 
8.7%
6 600
 
8.7%
3 600
 
8.7%
7 600
 
8.7%
8 600
 
8.7%
9 600
 
8.7%
4 600
 
8.7%
0 492
 
7.1%
Other values (17) 22
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6893
99.7%
Uppercase Letter 16
 
0.2%
Other Letter 4
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 3
18.8%
D 2
12.5%
E 2
12.5%
M 1
 
6.2%
N 1
 
6.2%
A 1
 
6.2%
X 1
 
6.2%
V 1
 
6.2%
R 1
 
6.2%
S 1
 
6.2%
Other values (2) 2
12.5%
Decimal Number
ValueCountFrequency (%)
1 1600
23.2%
2 601
 
8.7%
5 600
 
8.7%
6 600
 
8.7%
3 600
 
8.7%
7 600
 
8.7%
8 600
 
8.7%
9 600
 
8.7%
4 600
 
8.7%
0 492
 
7.1%
Other Letter
ValueCountFrequency (%)
관 1
25.0%
찰 1
25.0%
조 1
25.0%
사 1
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6895
99.7%
Latin 16
 
0.2%
Hangul 4
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 3
18.8%
D 2
12.5%
E 2
12.5%
M 1
 
6.2%
N 1
 
6.2%
A 1
 
6.2%
X 1
 
6.2%
V 1
 
6.2%
R 1
 
6.2%
S 1
 
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
1 1600
23.2%
2 601
 
8.7%
5 600
 
8.7%
6 600
 
8.7%
3 600
 
8.7%
7 600
 
8.7%
8 600
 
8.7%
9 600
 
8.7%
4 600
 
8.7%
0 492
 
7.1%
Hangul
ValueCountFrequency (%)
관 1
25.0%
찰 1
25.0%
조 1
25.0%
사 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6911
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1600
23.2%
2 601
 
8.7%
5 600
 
8.7%
6 600
 
8.7%
3 600
 
8.7%
7 600
 
8.7%
8 600
 
8.7%
9 600
 
8.7%
4 600
 
8.7%
0 492
 
7.1%
Other values (13) 18
 
0.3%
Hangul
ValueCountFrequency (%)
관 1
25.0%
찰 1
25.0%
조 1
25.0%
사 1
25.0%

Unnamed: 1
Text

Distinct1002
Distinct (%)50.0%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:16:17.737753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.3736264
Min length6

Characters and Unicode

Total characters12760
Distinct characters30
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row조사지점코드
2nd rowEXAMIN_SPOT_CD
3rd row01-029
4th row01-029
5th row01-033
ValueCountFrequency (%)
13-1131 2
 
0.1%
18-049 2
 
0.1%
17-3059 2
 
0.1%
19-019 2
 
0.1%
17-3060 2
 
0.1%
17-3073 2
 
0.1%
17-3078 2
 
0.1%
17-3085 2
 
0.1%
17-3101 2
 
0.1%
17-3107 2
 
0.1%
Other values (992) 1982
99.0%
2023-12-11T18:16:18.368435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2292
18.0%
1 2116
16.6%
- 2000
15.7%
2 1876
14.7%
3 1004
7.9%
4 742
 
5.8%
5 648
 
5.1%
7 540
 
4.2%
6 522
 
4.1%
9 504
 
3.9%
Other values (20) 516
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10740
84.2%
Dash Punctuation 2000
 
15.7%
Uppercase Letter 12
 
0.1%
Other Letter 6
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 1
8.3%
D 1
8.3%
C 1
8.3%
I 1
8.3%
O 1
8.3%
P 1
8.3%
S 1
8.3%
N 1
8.3%
M 1
8.3%
A 1
8.3%
Other values (2) 2
16.7%
Decimal Number
ValueCountFrequency (%)
0 2292
21.3%
1 2116
19.7%
2 1876
17.5%
3 1004
9.3%
4 742
 
6.9%
5 648
 
6.0%
7 540
 
5.0%
6 522
 
4.9%
9 504
 
4.7%
8 496
 
4.6%
Other Letter
ValueCountFrequency (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
사 1
16.7%
조 1
16.7%
드 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12742
99.9%
Latin 12
 
0.1%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2292
18.0%
1 2116
16.6%
- 2000
15.7%
2 1876
14.7%
3 1004
7.9%
4 742
 
5.8%
5 648
 
5.1%
7 540
 
4.2%
6 522
 
4.1%
9 504
 
4.0%
Other values (2) 498
 
3.9%
Latin
ValueCountFrequency (%)
T 1
8.3%
D 1
8.3%
C 1
8.3%
I 1
8.3%
O 1
8.3%
P 1
8.3%
S 1
8.3%
N 1
8.3%
M 1
8.3%
A 1
8.3%
Other values (2) 2
16.7%
Hangul
ValueCountFrequency (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
사 1
16.7%
조 1
16.7%
드 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12754
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2292
18.0%
1 2116
16.6%
- 2000
15.7%
2 1876
14.7%
3 1004
7.9%
4 742
 
5.8%
5 648
 
5.1%
7 540
 
4.2%
6 522
 
4.1%
9 504
 
4.0%
Other values (14) 510
 
4.0%
Hangul
ValueCountFrequency (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
사 1
16.7%
조 1
16.7%
드 1
16.7%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
1022
504 
1010
492 
1015
488 
1031
444 
1105
 
46
Other values (6)
 
29

Length

Max length10
Median length4
Mean length4.0029955
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row조사일자
3rd rowEXAMIN_DAY
4th row1022
5th row1022

Common Values

ValueCountFrequency (%)
1022 504
25.2%
1010 492
24.6%
1015 488
24.4%
1031 444
22.2%
1105 46
 
2.3%
1017 12
 
0.6%
1029 8
 
0.4%
1024 6
 
0.3%
<NA> 1
 
< 0.1%
조사일자 1
 
< 0.1%

Length

2023-12-11T18:16:18.545610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1022 504
25.2%
1010 492
24.6%
1015 488
24.4%
1031 444
22.2%
1105 46
 
2.3%
1017 12
 
0.6%
1029 8
 
0.4%
1024 6
 
0.3%
na 1
 
< 0.1%
조사일자 1
 
< 0.1%

Unnamed: 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
화
1046 
목
954 
<NA>
 
1
조사요일
 
1
EXAMIN_DATE
 
1

Length

Max length11
Median length1
Mean length1.007988
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row조사요일
3rd rowEXAMIN_DATE
4th row화
5th row화

Common Values

ValueCountFrequency (%)
화 1046
52.2%
목 954
47.6%
<NA> 1
 
< 0.1%
조사요일 1
 
< 0.1%
EXAMIN_DATE 1
 
< 0.1%

Length

2023-12-11T18:16:18.685711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:18.824137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화 1046
52.2%
목 954
47.6%
na 1
 
< 0.1%
조사요일 1
 
< 0.1%
examin_date 1
 
< 0.1%

Unnamed: 4
Text

Distinct130
Distinct (%)6.5%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:16:19.100644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length4
Mean length4.0064935
Min length4

Characters and Unicode

Total characters8021
Distinct characters25
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)1.4%

Sample

1st row조사시작시간
2nd rowEXAMIN_START_TM
3rd row0905
4th row1505
5th row0751
ValueCountFrequency (%)
1005 130
 
6.5%
0735 127
 
6.3%
1235 98
 
4.9%
1305 93
 
4.6%
0805 81
 
4.0%
0730 73
 
3.6%
0905 71
 
3.5%
1405 70
 
3.5%
1505 67
 
3.3%
1230 66
 
3.3%
Other values (120) 1126
56.2%
2023-12-11T18:16:19.551065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2795
34.8%
1 1352
16.9%
5 1309
16.3%
3 895
 
11.2%
7 332
 
4.1%
4 306
 
3.8%
2 292
 
3.6%
8 260
 
3.2%
9 246
 
3.1%
6 213
 
2.7%
Other values (15) 21
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8000
99.7%
Uppercase Letter 13
 
0.2%
Other Letter 6
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2795
34.9%
1 1352
16.9%
5 1309
16.4%
3 895
 
11.2%
7 332
 
4.2%
4 306
 
3.8%
2 292
 
3.6%
8 260
 
3.2%
9 246
 
3.1%
6 213
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
T 3
23.1%
A 2
15.4%
M 2
15.4%
E 1
 
7.7%
X 1
 
7.7%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
R 1
 
7.7%
Other Letter
ValueCountFrequency (%)
시 2
33.3%
간 1
16.7%
작 1
16.7%
사 1
16.7%
조 1
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8002
99.8%
Latin 13
 
0.2%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2795
34.9%
1 1352
16.9%
5 1309
16.4%
3 895
 
11.2%
7 332
 
4.1%
4 306
 
3.8%
2 292
 
3.6%
8 260
 
3.2%
9 246
 
3.1%
6 213
 
2.7%
Latin
ValueCountFrequency (%)
T 3
23.1%
A 2
15.4%
M 2
15.4%
E 1
 
7.7%
X 1
 
7.7%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
R 1
 
7.7%
Hangul
ValueCountFrequency (%)
시 2
33.3%
간 1
16.7%
작 1
16.7%
사 1
16.7%
조 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8015
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2795
34.9%
1 1352
16.9%
5 1309
16.3%
3 895
 
11.2%
7 332
 
4.1%
4 306
 
3.8%
2 292
 
3.6%
8 260
 
3.2%
9 246
 
3.1%
6 213
 
2.7%
Other values (10) 15
 
0.2%
Hangul
ValueCountFrequency (%)
시 2
33.3%
간 1
16.7%
작 1
16.7%
사 1
16.7%
조 1
16.7%

Unnamed: 5
Text

Distinct170
Distinct (%)8.5%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:16:19.877944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.0054945
Min length4

Characters and Unicode

Total characters8019
Distinct characters25
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)2.2%

Sample

1st row조사완료시간
2nd rowEXAMIN_END_TM
3rd row0955
4th row1555
5th row0856
ValueCountFrequency (%)
1055 101
 
5.0%
0955 74
 
3.7%
1455 71
 
3.5%
1355 62
 
3.1%
0825 58
 
2.9%
0855 57
 
2.8%
1130 48
 
2.4%
1655 44
 
2.2%
1555 44
 
2.2%
1325 42
 
2.1%
Other values (160) 1401
70.0%
2023-12-11T18:16:20.373886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1896
23.6%
5 1894
23.6%
1 1736
21.6%
3 611
 
7.6%
9 529
 
6.6%
4 398
 
5.0%
8 329
 
4.1%
2 310
 
3.9%
6 180
 
2.2%
7 117
 
1.5%
Other values (15) 19
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8000
99.8%
Uppercase Letter 11
 
0.1%
Other Letter 6
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1896
23.7%
5 1894
23.7%
1 1736
21.7%
3 611
 
7.6%
9 529
 
6.6%
4 398
 
5.0%
8 329
 
4.1%
2 310
 
3.9%
6 180
 
2.2%
7 117
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
N 2
18.2%
M 2
18.2%
E 2
18.2%
D 1
9.1%
A 1
9.1%
I 1
9.1%
X 1
9.1%
T 1
9.1%
Other Letter
ValueCountFrequency (%)
완 1
16.7%
간 1
16.7%
시 1
16.7%
료 1
16.7%
사 1
16.7%
조 1
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8002
99.8%
Latin 11
 
0.1%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1896
23.7%
5 1894
23.7%
1 1736
21.7%
3 611
 
7.6%
9 529
 
6.6%
4 398
 
5.0%
8 329
 
4.1%
2 310
 
3.9%
6 180
 
2.2%
7 117
 
1.5%
Latin
ValueCountFrequency (%)
N 2
18.2%
M 2
18.2%
E 2
18.2%
D 1
9.1%
A 1
9.1%
I 1
9.1%
X 1
9.1%
T 1
9.1%
Hangul
ValueCountFrequency (%)
완 1
16.7%
간 1
16.7%
시 1
16.7%
료 1
16.7%
사 1
16.7%
조 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8013
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1896
23.7%
5 1894
23.6%
1 1736
21.7%
3 611
 
7.6%
9 529
 
6.6%
4 398
 
5.0%
8 329
 
4.1%
2 310
 
3.9%
6 180
 
2.2%
7 117
 
1.5%
Other values (9) 13
 
0.2%
Hangul
ValueCountFrequency (%)
완 1
16.7%
간 1
16.7%
시 1
16.7%
료 1
16.7%
사 1
16.7%
조 1
16.7%

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing9
Missing (%)0.4%
Memory size15.8 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing7
Missing (%)0.3%
Memory size15.8 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing523
Missing (%)26.1%
Memory size15.8 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)1.7%
Memory size15.8 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25
Missing (%)1.2%
Memory size15.8 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing145
Missing (%)7.2%
Memory size15.8 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing109
Missing (%)5.4%
Memory size15.8 KiB

Unnamed: 13
Unsupported

REJECTED  UNSUPPORTED 

Missing4
Missing (%)0.2%
Memory size15.8 KiB

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)2.9%
Memory size15.8 KiB

Unnamed: 15
Unsupported

REJECTED  UNSUPPORTED 

Missing5
Missing (%)0.2%
Memory size15.8 KiB

Unnamed: 16
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing2001
Missing (%)99.9%
Memory size15.8 KiB
2023-12-11T18:16:20.541716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length4.5
Min length3

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row기타특이사항
2nd rowETC
ValueCountFrequency (%)
기타특이사항 1
50.0%
etc 1
50.0%
2023-12-11T18:16:21.095261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
11.1%
타 1
11.1%
특 1
11.1%
이 1
11.1%
사 1
11.1%
항 1
11.1%
E 1
11.1%
T 1
11.1%
C 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
66.7%
Uppercase Letter 3
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
특 1
16.7%
이 1
16.7%
사 1
16.7%
항 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
T 1
33.3%
C 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
66.7%
Latin 3
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
특 1
16.7%
이 1
16.7%
사 1
16.7%
항 1
16.7%
Latin
ValueCountFrequency (%)
E 1
33.3%
T 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
66.7%
ASCII 3
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
특 1
16.7%
이 1
16.7%
사 1
16.7%
항 1
16.7%
ASCII
ValueCountFrequency (%)
E 1
33.3%
T 1
33.3%
C 1
33.3%

Unnamed: 17
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
2013
2000 
<NA>
 
1
년도
 
1
YEAR
 
1

Length

Max length4
Median length4
Mean length3.9990015
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row년도
3rd rowYEAR
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 2000
99.9%
<NA> 1
 
< 0.1%
년도 1
 
< 0.1%
YEAR 1
 
< 0.1%

Length

2023-12-11T18:16:21.287758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:21.417275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 2000
99.9%
na 1
 
< 0.1%
년도 1
 
< 0.1%
year 1
 
< 0.1%

Unnamed: 18
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
주중
2000 
<NA>
 
1
주중주말구분
 
1
EXAMIN_WDAY_WEND
 
1

Length

Max length16
Median length2
Mean length2.009985
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row주중주말구분
3rd rowEXAMIN_WDAY_WEND
4th row주중
5th row주중

Common Values

ValueCountFrequency (%)
주중 2000
99.9%
<NA> 1
 
< 0.1%
주중주말구분 1
 
< 0.1%
EXAMIN_WDAY_WEND 1
 
< 0.1%

Length

2023-12-11T18:16:21.553801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:21.711224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주중 2000
99.9%
na 1
 
< 0.1%
주중주말구분 1
 
< 0.1%
examin_wday_wend 1
 
< 0.1%

Unnamed: 19
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
오전
1000 
오후
1000 
<NA>
 
1
오전오후구분
 
1
EXAMIN_AM_PM
 
1

Length

Max length12
Median length2
Mean length2.007988
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row오전오후구분
3rd rowEXAMIN_AM_PM
4th row오전
5th row오후

Common Values

ValueCountFrequency (%)
오전 1000
49.9%
오후 1000
49.9%
<NA> 1
 
< 0.1%
오전오후구분 1
 
< 0.1%
EXAMIN_AM_PM 1
 
< 0.1%

Length

2023-12-11T18:16:21.859005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:22.017467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오전 1000
49.9%
오후 1000
49.9%
na 1
 
< 0.1%
오전오후구분 1
 
< 0.1%
examin_am_pm 1
 
< 0.1%

Correlations

2023-12-11T18:16:22.123679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
Unnamed: 21.0001.0000.0001.0001.0000.919
Unnamed: 31.0001.0000.0001.0001.0000.982
Unnamed: 160.0000.0001.0000.0000.0000.000
Unnamed: 171.0001.0000.0001.0001.0001.000
Unnamed: 181.0001.0000.0001.0001.0001.000
Unnamed: 190.9190.9820.0001.0001.0001.000
2023-12-11T18:16:22.256869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 18Unnamed: 19Unnamed: 17
Unnamed: 21.0000.9980.9980.8140.998
Unnamed: 30.9981.0001.0000.8161.000
Unnamed: 180.9981.0001.0001.0001.000
Unnamed: 190.8140.8161.0001.0001.000
Unnamed: 170.9981.0001.0001.0001.000
2023-12-11T18:16:22.374277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 17Unnamed: 18Unnamed: 19
Unnamed: 21.0000.9980.9980.9980.814
Unnamed: 30.9981.0001.0001.0000.816
Unnamed: 170.9981.0001.0001.0001.000
Unnamed: 180.9981.0001.0001.0001.000
Unnamed: 190.8140.8161.0001.0001.000

Missing values

2023-12-11T18:16:15.561117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:16:15.822572image/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.
2023-12-11T18:16:16.078072image/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

유동인구_관찰조사_2013Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
0<NA><NA><NA><NA><NA><NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN<NA><NA><NA><NA>
1ID관찰조사조사지점코드조사일자조사요일조사시작시간조사완료시간남자유동인구수여성유동인구수20세미만유동인구수20대30대유동인구수40대50대유동인구수60대이상유동인구수정장착용유동인구수캐주얼착용유동인구수물건소지유동인구수빈손통행유동인구수기타특이사항년도주중주말구분오전오후구분
2ID_OBSERV_EXAMINEXAMIN_SPOT_CDEXAMIN_DAYEXAMIN_DATEEXAMIN_START_TMEXAMIN_END_TMMALEFEMALETWYO_BELOTWNT_THRTSFRTS_FFTSSXTS_ABOVESUIT_WEARCSL_WEARTHING_POSSESEMTHD_PASNGETCYEAREXAMIN_WDAY_WENDEXAMIN_AM_PM
3101-0291022화090509557142841317814<NA>2013주중오전
4201-0291022화15051555163873343442946<NA>2013주중오후
5301-0331022화07510856137NaN159NaN121225<NA>2013주중오전
6401-0331022화09211030127NaN1051NaN17215<NA>2013주중오전
7501-0351022화09401100395256329537721878<NA>2013주중오전
8601-0351022화131015251238381175711659451118<NA>2013주중오후
9701-0361015화0805085563480832487812634188<NA>2013주중오전
유동인구_관찰조사_2013Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
1993199125-4801015화080508591019296NaN114213<NA>2013주중오전
1994199225-4801015화10051059311NaN369NaN7117<NA>2013주중오전
1995199325-8141015화0805085921266221211341726<NA>2013주중오전
1996199425-8141015화100510598123832317513<NA>2013주중오전
1997199525-8181022화0800085914141763119217<NA>2013주중오전
1998199625-8181022화1000105995NaN795NaN12714<NA>2013주중오전
1999199725-8201015화130513592716NaN81331222225<NA>2013주중오후
2000199825-8201015화15061559178NaN111482181023<NA>2013주중오후
2001199925-8221015화1405145521113594727<NA>2013주중오후
2002200025-8221015화1605165557643NaN11359<NA>2013주중오후