Overview

Dataset statistics

Number of variables20
Number of observations2003
Missing cells2027
Missing cells (%)5.1%
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 (96.3%)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: 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 09:15:54.967152
Analysis finished2023-12-11 09:15:56.842958
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동인구_관찰조사_2015
Text

Distinct2002
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:15:57.249333image/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%
2023-12-11T18:15:57.865340image/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
2023-12-11T18:15:58.280548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.2707293
Min length6

Characters and Unicode

Total characters12554
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 row01-003
4th row01-003
5th row01-005
ValueCountFrequency (%)
14-012 2
 
0.1%
19-005 2
 
0.1%
18-052 2
 
0.1%
19-052 2
 
0.1%
18-2005 2
 
0.1%
18-2009 2
 
0.1%
18-2018 2
 
0.1%
18-2021 2
 
0.1%
18-2034 2
 
0.1%
18-2046 2
 
0.1%
Other values (992) 1982
99.0%
2023-12-11T18:15:58.769384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2558
20.4%
- 2000
15.9%
1 1996
15.9%
2 1852
14.8%
3 886
 
7.1%
4 730
 
5.8%
5 626
 
5.0%
6 494
 
3.9%
8 482
 
3.8%
7 476
 
3.8%
Other values (20) 454
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10534
83.9%
Dash Punctuation 2000
 
15.9%
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 2558
24.3%
1 1996
18.9%
2 1852
17.6%
3 886
 
8.4%
4 730
 
6.9%
5 626
 
5.9%
6 494
 
4.7%
8 482
 
4.6%
7 476
 
4.5%
9 434
 
4.1%
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 12536
99.9%
Latin 12
 
0.1%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2558
20.4%
- 2000
16.0%
1 1996
15.9%
2 1852
14.8%
3 886
 
7.1%
4 730
 
5.8%
5 626
 
5.0%
6 494
 
3.9%
8 482
 
3.8%
7 476
 
3.8%
Other values (2) 436
 
3.5%
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 12548
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2558
20.4%
- 2000
15.9%
1 1996
15.9%
2 1852
14.8%
3 886
 
7.1%
4 730
 
5.8%
5 626
 
5.0%
6 494
 
3.9%
8 482
 
3.8%
7 476
 
3.8%
Other values (14) 448
 
3.6%
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 

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
1013
540 
1020
510 
1027
494 
1006
440 
1029
 
8
Other values (5)
 
11

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 row1013
5th row1013

Common Values

ValueCountFrequency (%)
1013 540
27.0%
1020 510
25.5%
1027 494
24.7%
1006 440
22.0%
1029 8
 
0.4%
1022 6
 
0.3%
1008 2
 
0.1%
<NA> 1
 
< 0.1%
조사일자 1
 
< 0.1%
EXAMIN_DAY 1
 
< 0.1%

Length

2023-12-11T18:15:58.970129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:15:59.102503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1013 540
27.0%
1020 510
25.5%
1027 494
24.7%
1006 440
22.0%
1029 8
 
0.4%
1022 6
 
0.3%
1008 2
 
0.1%
na 1
 
< 0.1%
조사일자 1
 
< 0.1%
examin_day 1
 
< 0.1%

Unnamed: 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
화
1984 
목
 
16
<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 1984
99.1%
목 16
 
0.8%
<NA> 1
 
< 0.1%
조사요일 1
 
< 0.1%
EXAMIN_DATE 1
 
< 0.1%

Length

2023-12-11T18:15:59.258987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:15:59.370251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화 1984
99.1%
목 16
 
0.8%
na 1
 
< 0.1%
조사요일 1
 
< 0.1%
examin_date 1
 
< 0.1%

Unnamed: 4
Text

Distinct145
Distinct (%)7.2%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:15:59.641687image/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

Unique19 ?
Unique (%)0.9%

Sample

1st row조사시작시간
2nd rowEXAMIN_START_TM
3rd row0735
4th row1352
5th row0805
ValueCountFrequency (%)
0735 116
 
5.8%
0805 95
 
4.7%
0905 94
 
4.7%
1505 82
 
4.1%
1605 59
 
2.9%
1405 55
 
2.7%
0900 55
 
2.7%
0800 51
 
2.5%
0730 48
 
2.4%
1305 45
 
2.2%
Other values (135) 1302
65.0%
2023-12-11T18:16:00.122266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2785
34.7%
1 1317
16.4%
5 1248
15.6%
3 725
 
9.0%
7 370
 
4.6%
8 368
 
4.6%
4 367
 
4.6%
9 292
 
3.6%
2 279
 
3.5%
6 249
 
3.1%
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 2785
34.8%
1 1317
16.5%
5 1248
15.6%
3 725
 
9.1%
7 370
 
4.6%
8 368
 
4.6%
4 367
 
4.6%
9 292
 
3.6%
2 279
 
3.5%
6 249
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
T 3
23.1%
A 2
15.4%
M 2
15.4%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
X 1
 
7.7%
R 1
 
7.7%
E 1
 
7.7%
Other Letter
ValueCountFrequency (%)
시 2
33.3%
조 1
16.7%
사 1
16.7%
작 1
16.7%
간 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 2785
34.8%
1 1317
16.5%
5 1248
15.6%
3 725
 
9.1%
7 370
 
4.6%
8 368
 
4.6%
4 367
 
4.6%
9 292
 
3.6%
2 279
 
3.5%
6 249
 
3.1%
Latin
ValueCountFrequency (%)
T 3
23.1%
A 2
15.4%
M 2
15.4%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
X 1
 
7.7%
R 1
 
7.7%
E 1
 
7.7%
Hangul
ValueCountFrequency (%)
시 2
33.3%
조 1
16.7%
사 1
16.7%
작 1
16.7%
간 1
16.7%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2785
34.7%
1 1317
16.4%
5 1248
15.6%
3 725
 
9.0%
7 370
 
4.6%
8 368
 
4.6%
4 367
 
4.6%
9 292
 
3.6%
2 279
 
3.5%
6 249
 
3.1%
Other values (10) 15
 
0.2%
Hangul
ValueCountFrequency (%)
시 2
33.3%
조 1
16.7%
사 1
16.7%
작 1
16.7%
간 1
16.7%

Unnamed: 5
Text

Distinct172
Distinct (%)8.6%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2023-12-11T18:16:00.460576image/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

Unique27 ?
Unique (%)1.3%

Sample

1st row조사완료시간
2nd rowEXAMIN_END_TM
3rd row0825
4th row1457
5th row0900
ValueCountFrequency (%)
1000 70
 
3.5%
0955 68
 
3.4%
0930 50
 
2.5%
1600 47
 
2.3%
1555 46
 
2.3%
0855 44
 
2.2%
1430 42
 
2.1%
1610 42
 
2.1%
1500 41
 
2.0%
1055 40
 
2.0%
Other values (162) 1512
75.5%
2023-12-11T18:16:00.937992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2419
30.2%
1 1894
23.6%
5 1395
17.4%
9 454
 
5.7%
3 433
 
5.4%
4 394
 
4.9%
8 300
 
3.7%
6 296
 
3.7%
2 239
 
3.0%
7 176
 
2.2%
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 2419
30.2%
1 1894
23.7%
5 1395
17.4%
9 454
 
5.7%
3 433
 
5.4%
4 394
 
4.9%
8 300
 
3.8%
6 296
 
3.7%
2 239
 
3.0%
7 176
 
2.2%
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 2419
30.2%
1 1894
23.7%
5 1395
17.4%
9 454
 
5.7%
3 433
 
5.4%
4 394
 
4.9%
8 300
 
3.7%
6 296
 
3.7%
2 239
 
3.0%
7 176
 
2.2%
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 2419
30.2%
1 1894
23.6%
5 1395
17.4%
9 454
 
5.7%
3 433
 
5.4%
4 394
 
4.9%
8 300
 
3.7%
6 296
 
3.7%
2 239
 
3.0%
7 176
 
2.2%
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 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

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

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 10
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 11
Unsupported

REJECTED  UNSUPPORTED 

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

Unnamed: 12
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 13
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 14
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)0.1%
Memory size15.8 KiB

Unnamed: 15
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size15.8 KiB

Unnamed: 16
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing2001
Missing (%)99.9%
Memory size15.8 KiB
2023-12-11T18:16:01.100847image/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%
2023-12-11T18:16:01.357112image/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
2015
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 row2015
5th row2015

Common Values

ValueCountFrequency (%)
2015 2000
99.9%
<NA> 1
 
< 0.1%
년도 1
 
< 0.1%
YEAR 1
 
< 0.1%

Length

2023-12-11T18:16:01.487028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:01.600102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015 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

2023-12-11T18:16:01.745885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:01.873153image/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

2023-12-11T18:16:02.006654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:16:02.122079image/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

2023-12-11T18:16:02.221235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
Unnamed: 21.0001.0000.0001.0001.0000.896
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: 190.8960.9820.0001.0001.0001.000
2023-12-11T18:16:02.339994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 18Unnamed: 19Unnamed: 17
Unnamed: 21.0000.9990.9980.8150.998
Unnamed: 30.9991.0001.0000.8161.000
Unnamed: 180.9981.0001.0001.0001.000
Unnamed: 190.8150.8161.0001.0001.000
Unnamed: 170.9981.0001.0001.0001.000
2023-12-11T18:16:02.440186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 17Unnamed: 18Unnamed: 19
Unnamed: 21.0000.9990.9980.9980.815
Unnamed: 30.9991.0001.0001.0000.816
Unnamed: 170.9981.0001.0001.0001.000
Unnamed: 180.9981.0001.0001.0001.000
Unnamed: 190.8150.8161.0001.0001.000

Missing values

2023-12-11T18:15:55.934581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:15:56.256876image/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.
2023-12-11T18:15:56.561460image/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_2015Unnamed: 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
3101-0031013화073508257407201618<NA>2015주중오전
4201-0031013화1352145735035207110<NA>2015주중오후
5301-0051027화08050900837531011212<NA>2015주중오전
6401-0051027화13351425460152110315<NA>2015주중오후
7501-0081013화090509556914258749<NA>2015주중오전
8601-0081013화141015555434731514769<NA>2015주중오후
9701-0091006화0900100041018311907<NA>2015주중오전
유동인구_관찰조사_2015Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
1993199125-2421006화07350840191421193521617<NA>2015주중오전
1994199225-2421006화13051440142609113427623<NA>2015주중오후
1995199325-4081027화082509307546582721938821650<NA>2015주중오전
1996199425-4081027화13061406455701922368861773<NA>2015주중오후
1997199525-4301027화0806091029513351111675533<NA>2015주중오전
1998199625-4301027화1406151029881612524231333785<NA>2015주중오후
1999199725-4341027화074008407311257787<NA>2015주중오전
2000199825-4341027화183019306502342637<NA>2015주중오후
2001199925-4631027화0906095615173191587281127<NA>2015주중오전
2002200025-4631027화12401440131921281511261026<NA>2015주중오후