Overview

Dataset statistics

Number of variables37
Number of observations1003
Missing cells12081
Missing cells (%)32.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory290.1 KiB
Average record size in memory296.1 B

Variable types

Text21
Categorical16

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21707/F/1/datasetView.do

Alerts

Unnamed: 9 is highly imbalanced (70.4%)Imbalance
Unnamed: 10 is highly imbalanced (58.3%)Imbalance
Unnamed: 11 is highly imbalanced (78.8%)Imbalance
Unnamed: 13 is highly imbalanced (58.8%)Imbalance
Unnamed: 14 is highly imbalanced (57.2%)Imbalance
Unnamed: 15 is highly imbalanced (65.0%)Imbalance
Unnamed: 16 is highly imbalanced (66.9%)Imbalance
Unnamed: 17 is highly imbalanced (56.3%)Imbalance
Unnamed: 19 is highly imbalanced (66.3%)Imbalance
Unnamed: 20 is highly imbalanced (57.7%)Imbalance
Unnamed: 35 is highly imbalanced (98.3%)Imbalance
Unnamed: 36 is highly imbalanced (98.3%)Imbalance
Unnamed: 3 has 22 (2.2%) missing valuesMissing
Unnamed: 18 has 1001 (99.8%) missing valuesMissing
Unnamed: 21 has 1001 (99.8%) missing valuesMissing
Unnamed: 22 has 1001 (99.8%) missing valuesMissing
Unnamed: 23 has 1001 (99.8%) missing valuesMissing
Unnamed: 24 has 1001 (99.8%) missing valuesMissing
Unnamed: 25 has 1001 (99.8%) missing valuesMissing
Unnamed: 26 has 1001 (99.8%) missing valuesMissing
Unnamed: 27 has 1001 (99.8%) missing valuesMissing
Unnamed: 28 has 1001 (99.8%) missing valuesMissing
Unnamed: 29 has 1001 (99.8%) missing valuesMissing
Unnamed: 30 has 1001 (99.8%) missing valuesMissing
Unnamed: 31 has 1001 (99.8%) missing valuesMissing
Unnamed: 32 has 14 (1.4%) missing valuesMissing
Unnamed: 33 has 14 (1.4%) missing valuesMissing
Unnamed: 34 has 14 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-04-17 18:41:52.971138
Analysis finished2024-04-17 18:41:54.036915
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동인구_조사지점정보_2013
Text

Distinct1002
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-18T03:41:54.277552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.3772455
Min length6

Characters and Unicode

Total characters6390
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

Unique1002 ?
Unique (%)100.0%

Sample

1st row조사지점코드
2nd rowEXAMIN_SPOT_CD
3rd row01-029
4th row01-033
5th row01-035
ValueCountFrequency (%)
01-065 1
 
0.1%
18-049 1
 
0.1%
17-3059 1
 
0.1%
19-019 1
 
0.1%
17-3060 1
 
0.1%
17-3073 1
 
0.1%
17-3078 1
 
0.1%
17-3085 1
 
0.1%
17-3101 1
 
0.1%
17-3107 1
 
0.1%
Other values (992) 992
99.0%
2024-04-18T03:41:54.694616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1146
17.9%
1 1058
16.6%
- 1000
15.6%
2 938
14.7%
3 502
7.9%
4 371
 
5.8%
5 324
 
5.1%
7 270
 
4.2%
6 261
 
4.1%
9 252
 
3.9%
Other values (20) 268
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5370
84.0%
Dash Punctuation 1000
 
15.6%
Uppercase Letter 12
 
0.2%
Other Letter 6
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 1
8.3%
D 1
8.3%
S 1
8.3%
T 1
8.3%
O 1
8.3%
P 1
8.3%
N 1
8.3%
I 1
8.3%
M 1
8.3%
A 1
8.3%
Other values (2) 2
16.7%
Decimal Number
ValueCountFrequency (%)
0 1146
21.3%
1 1058
19.7%
2 938
17.5%
3 502
9.3%
4 371
 
6.9%
5 324
 
6.0%
7 270
 
5.0%
6 261
 
4.9%
9 252
 
4.7%
8 248
 
4.6%
Other Letter
ValueCountFrequency (%)
점 1
16.7%
조 1
16.7%
사 1
16.7%
지 1
16.7%
코 1
16.7%
드 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6372
99.7%
Latin 12
 
0.2%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1146
18.0%
1 1058
16.6%
- 1000
15.7%
2 938
14.7%
3 502
7.9%
4 371
 
5.8%
5 324
 
5.1%
7 270
 
4.2%
6 261
 
4.1%
9 252
 
4.0%
Other values (2) 250
 
3.9%
Latin
ValueCountFrequency (%)
C 1
8.3%
D 1
8.3%
S 1
8.3%
T 1
8.3%
O 1
8.3%
P 1
8.3%
N 1
8.3%
I 1
8.3%
M 1
8.3%
A 1
8.3%
Other values (2) 2
16.7%
Hangul
ValueCountFrequency (%)
점 1
16.7%
조 1
16.7%
사 1
16.7%
지 1
16.7%
코 1
16.7%
드 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6384
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1146
18.0%
1 1058
16.6%
- 1000
15.7%
2 938
14.7%
3 502
7.9%
4 371
 
5.8%
5 324
 
5.1%
7 270
 
4.2%
6 261
 
4.1%
9 252
 
3.9%
Other values (14) 262
 
4.1%
Hangul
ValueCountFrequency (%)
점 1
16.7%
조 1
16.7%
사 1
16.7%
지 1
16.7%
코 1
16.7%
드 1
16.7%

Unnamed: 1
Text

Distinct978
Distinct (%)97.6%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-18T03:41:54.887940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length7.2015968
Min length2

Characters and Unicode

Total characters7216
Distinct characters630
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique963 ?
Unique (%)96.1%

Sample

1st row조사지점명
2nd rowEXAMIN_SPOT_NM
3rd rowKFC
4th row오복영양치킨
5th row영안빌딩(미샤옆)
ValueCountFrequency (%)
gs25 6
 
0.6%
롯데리아 4
 
0.4%
김밥천국 3
 
0.3%
커피빈 3
 
0.3%
파리바게트 3
 
0.3%
신한은행 3
 
0.3%
t-world 3
 
0.3%
신세계백화점 2
 
0.2%
뚜레쥬르 2
 
0.2%
한독안경 2
 
0.2%
Other values (966) 971
96.9%
2024-04-18T03:41:55.164634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 151
 
2.1%
빌 127
 
1.8%
딩 98
 
1.4%
리 98
 
1.4%
이 97
 
1.3%
점 95
 
1.3%
트 93
 
1.3%
지 92
 
1.3%
구 91
 
1.3%
대 82
 
1.1%
Other values (620) 6192
85.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6349
88.0%
Uppercase Letter 321
 
4.4%
Decimal Number 214
 
3.0%
Lowercase Letter 171
 
2.4%
Close Punctuation 55
 
0.8%
Open Punctuation 55
 
0.8%
Other Punctuation 29
 
0.4%
Dash Punctuation 17
 
0.2%
Other Symbol 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 151
 
2.4%
빌 127
 
2.0%
딩 98
 
1.5%
리 98
 
1.5%
이 97
 
1.5%
점 95
 
1.5%
트 93
 
1.5%
지 92
 
1.4%
구 91
 
1.4%
대 82
 
1.3%
Other values (551) 5325
83.9%
Uppercase Letter
ValueCountFrequency (%)
S 42
 
13.1%
K 22
 
6.9%
T 21
 
6.5%
G 20
 
6.2%
E 19
 
5.9%
A 17
 
5.3%
O 17
 
5.3%
N 17
 
5.3%
C 16
 
5.0%
B 14
 
4.4%
Other values (15) 116
36.1%
Lowercase Letter
ValueCountFrequency (%)
o 22
12.9%
e 20
11.7%
s 14
 
8.2%
r 12
 
7.0%
a 12
 
7.0%
l 12
 
7.0%
d 9
 
5.3%
i 9
 
5.3%
n 8
 
4.7%
c 7
 
4.1%
Other values (13) 46
26.9%
Decimal Number
ValueCountFrequency (%)
1 54
25.2%
2 42
19.6%
5 29
13.6%
3 27
12.6%
0 21
 
9.8%
4 14
 
6.5%
9 9
 
4.2%
7 7
 
3.3%
8 6
 
2.8%
6 5
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 10
34.5%
, 7
24.1%
& 7
24.1%
/ 3
 
10.3%
' 1
 
3.4%
: 1
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6349
88.0%
Latin 492
 
6.8%
Common 372
 
5.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 151
 
2.4%
빌 127
 
2.0%
딩 98
 
1.5%
리 98
 
1.5%
이 97
 
1.5%
점 95
 
1.5%
트 93
 
1.5%
지 92
 
1.4%
구 91
 
1.4%
대 82
 
1.3%
Other values (549) 5325
83.9%
Latin
ValueCountFrequency (%)
S 42
 
8.5%
o 22
 
4.5%
K 22
 
4.5%
T 21
 
4.3%
e 20
 
4.1%
G 20
 
4.1%
E 19
 
3.9%
A 17
 
3.5%
O 17
 
3.5%
N 17
 
3.5%
Other values (38) 275
55.9%
Common
ValueCountFrequency (%)
) 55
14.8%
( 55
14.8%
1 54
14.5%
2 42
11.3%
5 29
7.8%
3 27
7.3%
0 21
 
5.6%
- 17
 
4.6%
4 14
 
3.8%
. 10
 
2.7%
Other values (10) 48
12.9%
Han
ValueCountFrequency (%)
昌 1
33.3%
原 1
33.3%
內 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6346
87.9%
ASCII 864
 
12.0%
None 3
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 151
 
2.4%
빌 127
 
2.0%
딩 98
 
1.5%
리 98
 
1.5%
이 97
 
1.5%
점 95
 
1.5%
트 93
 
1.5%
지 92
 
1.4%
구 91
 
1.4%
대 82
 
1.3%
Other values (548) 5322
83.9%
ASCII
ValueCountFrequency (%)
) 55
 
6.4%
( 55
 
6.4%
1 54
 
6.2%
2 42
 
4.9%
S 42
 
4.9%
5 29
 
3.4%
3 27
 
3.1%
o 22
 
2.5%
K 22
 
2.5%
0 21
 
2.4%
Other values (58) 495
57.3%
None
ValueCountFrequency (%)
㈜ 3
100.0%
CJK
ValueCountFrequency (%)
昌 1
33.3%
原 1
33.3%
內 1
33.3%

Unnamed: 2
Categorical

Distinct28
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
11010
 
68
11020
 
63
11230
 
63
11110
 
61
11220
 
61
Other values (23)
687 

Length

Max length5
Median length5
Mean length4.9760718
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row구코드
3rd rowGU_CD
4th row11010
5th row11010

Common Values

ValueCountFrequency (%)
11010 68
 
6.8%
11020 63
 
6.3%
11230 63
 
6.3%
11110 61
 
6.1%
11220 61
 
6.1%
11190 54
 
5.4%
11240 49
 
4.9%
11170 43
 
4.3%
11070 41
 
4.1%
11150 38
 
3.8%
Other values (18) 462
46.1%

Length

2024-04-18T03:41:55.274472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11010 68
 
6.8%
11020 63
 
6.3%
11230 63
 
6.3%
11110 61
 
6.1%
11220 61
 
6.1%
11190 54
 
5.4%
11240 49
 
4.9%
11170 43
 
4.3%
11070 41
 
4.1%
11150 38
 
3.8%
Other values (18) 462
46.1%

Unnamed: 3
Text

MISSING 

Distinct322
Distinct (%)32.8%
Missing22
Missing (%)2.2%
Memory size8.0 KiB
2024-04-18T03:41:55.544271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9959225
Min length3

Characters and Unicode

Total characters6863
Distinct characters19
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

Unique107 ?
Unique (%)10.9%

Sample

1st row동코드
2nd rowDONG_CD
3rd row1101064
4th row1101061
5th row1101061
ValueCountFrequency (%)
1101061 26
 
2.7%
1102055 21
 
2.1%
1119054 15
 
1.5%
1107062 15
 
1.5%
1111079 13
 
1.3%
1102052 12
 
1.2%
1123064 11
 
1.1%
1113075 11
 
1.1%
1101053 10
 
1.0%
1101054 10
 
1.0%
Other values (312) 837
85.3%
2024-04-18T03:41:55.933529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2612
38.1%
0 1445
21.1%
5 577
 
8.4%
2 564
 
8.2%
6 480
 
7.0%
7 384
 
5.6%
4 242
 
3.5%
3 233
 
3.4%
8 159
 
2.3%
9 157
 
2.3%
Other values (9) 10
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6853
99.9%
Uppercase Letter 6
 
0.1%
Other Letter 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2612
38.1%
0 1445
21.1%
5 577
 
8.4%
2 564
 
8.2%
6 480
 
7.0%
7 384
 
5.6%
4 242
 
3.5%
3 233
 
3.4%
8 159
 
2.3%
9 157
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
33.3%
O 1
16.7%
N 1
16.7%
G 1
16.7%
C 1
16.7%
Other Letter
ValueCountFrequency (%)
동 1
33.3%
코 1
33.3%
드 1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6854
99.9%
Latin 6
 
0.1%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2612
38.1%
0 1445
21.1%
5 577
 
8.4%
2 564
 
8.2%
6 480
 
7.0%
7 384
 
5.6%
4 242
 
3.5%
3 233
 
3.4%
8 159
 
2.3%
9 157
 
2.3%
Latin
ValueCountFrequency (%)
D 2
33.3%
O 1
16.7%
N 1
16.7%
G 1
16.7%
C 1
16.7%
Hangul
ValueCountFrequency (%)
동 1
33.3%
코 1
33.3%
드 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6860
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2612
38.1%
0 1445
21.1%
5 577
 
8.4%
2 564
 
8.2%
6 480
 
7.0%
7 384
 
5.6%
4 242
 
3.5%
3 233
 
3.4%
8 159
 
2.3%
9 157
 
2.3%
Other values (6) 7
 
0.1%
Hangul
ValueCountFrequency (%)
동 1
33.3%
코 1
33.3%
드 1
33.3%

Unnamed: 4
Text

Distinct620
Distinct (%)61.9%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-18T03:41:56.238188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.8742515
Min length1

Characters and Unicode

Total characters2880
Distinct characters21
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

Unique419 ?
Unique (%)41.8%

Sample

1st row주번지
2nd rowBUNJI
3rd row1
4th row5
5th row84
ValueCountFrequency (%)
1 13
 
1.3%
35 7
 
0.7%
27 7
 
0.7%
5 7
 
0.7%
18 7
 
0.7%
25 6
 
0.6%
19 6
 
0.6%
2 5
 
0.5%
3 5
 
0.5%
72 5
 
0.5%
Other values (610) 935
93.2%
2024-04-18T03:41:56.651711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 511
17.7%
3 335
11.6%
2 308
10.7%
5 277
9.6%
4 269
9.3%
6 253
8.8%
0 228
7.9%
7 224
7.8%
8 209
7.3%
9 195
 
6.8%
Other values (11) 71
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2809
97.5%
Dash Punctuation 61
 
2.1%
Uppercase Letter 5
 
0.2%
Other Letter 4
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 511
18.2%
3 335
11.9%
2 308
11.0%
5 277
9.9%
4 269
9.6%
6 253
9.0%
0 228
8.1%
7 224
8.0%
8 209
7.4%
9 195
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
20.0%
U 1
20.0%
N 1
20.0%
J 1
20.0%
I 1
20.0%
Other Letter
ValueCountFrequency (%)
주 1
25.0%
번 1
25.0%
지 1
25.0%
산 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2871
99.7%
Latin 5
 
0.2%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 511
17.8%
3 335
11.7%
2 308
10.7%
5 277
9.6%
4 269
9.4%
6 253
8.8%
0 228
7.9%
7 224
7.8%
8 209
7.3%
9 195
 
6.8%
Other values (2) 62
 
2.2%
Latin
ValueCountFrequency (%)
B 1
20.0%
U 1
20.0%
N 1
20.0%
J 1
20.0%
I 1
20.0%
Hangul
ValueCountFrequency (%)
주 1
25.0%
번 1
25.0%
지 1
25.0%
산 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2876
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 511
17.8%
3 335
11.6%
2 308
10.7%
5 277
9.6%
4 269
9.4%
6 253
8.8%
0 228
7.9%
7 224
7.8%
8 209
7.3%
9 195
 
6.8%
Other values (7) 67
 
2.3%
Hangul
ValueCountFrequency (%)
주 1
25.0%
번 1
25.0%
지 1
25.0%
산 1
25.0%

Unnamed: 5
Text

Distinct114
Distinct (%)11.4%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-18T03:41:56.843803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.4051896
Min length1

Characters and Unicode

Total characters1408
Distinct characters22
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)5.2%

Sample

1st row부번지
2nd rowBUBUN
3rd row27
4th row1
5th row1
ValueCountFrequency (%)
0 255
25.4%
1 127
 
12.7%
2 51
 
5.1%
5 43
 
4.3%
3 43
 
4.3%
4 29
 
2.9%
7 28
 
2.8%
8 26
 
2.6%
6 23
 
2.3%
9 19
 
1.9%
Other values (104) 358
35.7%
2024-04-18T03:41:57.145338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 333
23.7%
0 304
21.6%
2 169
12.0%
3 119
 
8.5%
5 110
 
7.8%
4 101
 
7.2%
8 77
 
5.5%
7 69
 
4.9%
6 61
 
4.3%
9 51
 
3.6%
Other values (12) 14
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1394
99.0%
Other Letter 9
 
0.6%
Uppercase Letter 5
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 333
23.9%
0 304
21.8%
2 169
12.1%
3 119
 
8.5%
5 110
 
7.9%
4 101
 
7.2%
8 77
 
5.5%
7 69
 
4.9%
6 61
 
4.4%
9 51
 
3.7%
Other Letter
ValueCountFrequency (%)
영 1
11.1%
빌 1
11.1%
웰 1
11.1%
자 1
11.1%
번 1
11.1%
신 1
11.1%
지 1
11.1%
부 1
11.1%
딩 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
U 2
40.0%
N 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1394
99.0%
Hangul 9
 
0.6%
Latin 5
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 333
23.9%
0 304
21.8%
2 169
12.1%
3 119
 
8.5%
5 110
 
7.9%
4 101
 
7.2%
8 77
 
5.5%
7 69
 
4.9%
6 61
 
4.4%
9 51
 
3.7%
Hangul
ValueCountFrequency (%)
영 1
11.1%
빌 1
11.1%
웰 1
11.1%
자 1
11.1%
번 1
11.1%
신 1
11.1%
지 1
11.1%
부 1
11.1%
딩 1
11.1%
Latin
ValueCountFrequency (%)
B 2
40.0%
U 2
40.0%
N 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1399
99.4%
Hangul 9
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 333
23.8%
0 304
21.7%
2 169
12.1%
3 119
 
8.5%
5 110
 
7.9%
4 101
 
7.2%
8 77
 
5.5%
7 69
 
4.9%
6 61
 
4.4%
9 51
 
3.6%
Other values (3) 5
 
0.4%
Hangul
ValueCountFrequency (%)
영 1
11.1%
빌 1
11.1%
웰 1
11.1%
자 1
11.1%
번 1
11.1%
신 1
11.1%
지 1
11.1%
부 1
11.1%
딩 1
11.1%

Unnamed: 6
Text

Distinct996
Distinct (%)99.4%
Missing1
Missing (%)0.1%
Memory size8.0 KiB
2024-04-18T03:41:57.461164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.3832335
Min length3

Characters and Unicode

Total characters8400
Distinct characters252
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

Unique990 ?
Unique (%)98.8%

Sample

1st row도로명
2nd rowROAD_NM
3rd row대학로 120
4th row종로구 종로 16길 12
5th row종로구 종로 74
ValueCountFrequency (%)
동일로 28
 
1.3%
천호대로 17
 
0.8%
12 14
 
0.6%
도봉로 14
 
0.6%
13 14
 
0.6%
종로 13
 
0.6%
남부순환로 13
 
0.6%
7 13
 
0.6%
강남대로 12
 
0.5%
18 12
 
0.5%
Other values (1002) 2070
93.2%
2024-04-18T03:41:57.897297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1218
 
14.5%
로 986
 
11.7%
1 614
 
7.3%
2 447
 
5.3%
길 353
 
4.2%
3 345
 
4.1%
5 286
 
3.4%
4 281
 
3.3%
7 239
 
2.8%
6 234
 
2.8%
Other values (242) 3397
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3969
47.2%
Decimal Number 3082
36.7%
Space Separator 1218
 
14.5%
Dash Punctuation 77
 
0.9%
Close Punctuation 22
 
0.3%
Open Punctuation 22
 
0.3%
Uppercase Letter 6
 
0.1%
Other Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 986
24.8%
길 353
 
8.9%
대 148
 
3.7%
동 122
 
3.1%
산 69
 
1.7%
천 51
 
1.3%
서 47
 
1.2%
구 47
 
1.2%
일 44
 
1.1%
지 43
 
1.1%
Other values (219) 2059
51.9%
Decimal Number
ValueCountFrequency (%)
1 614
19.9%
2 447
14.5%
3 345
11.2%
5 286
9.3%
4 281
9.1%
7 239
 
7.8%
6 234
 
7.6%
8 233
 
7.6%
9 213
 
6.9%
0 190
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
M 1
16.7%
N 1
16.7%
A 1
16.7%
O 1
16.7%
R 1
16.7%
Space Separator
ValueCountFrequency (%)
1218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4425
52.7%
Hangul 3969
47.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 986
24.8%
길 353
 
8.9%
대 148
 
3.7%
동 122
 
3.1%
산 69
 
1.7%
천 51
 
1.3%
서 47
 
1.2%
구 47
 
1.2%
일 44
 
1.1%
지 43
 
1.1%
Other values (219) 2059
51.9%
Common
ValueCountFrequency (%)
1218
27.5%
1 614
13.9%
2 447
 
10.1%
3 345
 
7.8%
5 286
 
6.5%
4 281
 
6.4%
7 239
 
5.4%
6 234
 
5.3%
8 233
 
5.3%
9 213
 
4.8%
Other values (7) 315
 
7.1%
Latin
ValueCountFrequency (%)
D 1
16.7%
M 1
16.7%
N 1
16.7%
A 1
16.7%
O 1
16.7%
R 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4431
52.8%
Hangul 3969
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1218
27.5%
1 614
13.9%
2 447
 
10.1%
3 345
 
7.8%
5 286
 
6.5%
4 281
 
6.3%
7 239
 
5.4%
6 234
 
5.3%
8 233
 
5.3%
9 213
 
4.8%
Other values (13) 321
 
7.2%
Hangul
ValueCountFrequency (%)
로 986
24.8%
길 353
 
8.9%
대 148
 
3.7%
동 122
 
3.1%
산 69
 
1.7%
천 51
 
1.3%
서 47
 
1.2%
구 47
 
1.2%
일 44
 
1.1%
지 43
 
1.1%
Other values (219) 2059
51.9%

Unnamed: 7
Categorical

Distinct23
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
3
207 
4
169 
2
166 
5
147 
6
97 
Other values (18)
217 

Length

Max length8
Median length1
Mean length1.0498504
Min length1

Unique

Unique9 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row보도너비
3rd rowFTPTH_BT
4th row4
5th row6

Common Values

ValueCountFrequency (%)
3 207
20.6%
4 169
16.8%
2 166
16.6%
5 147
14.7%
6 97
9.7%
7 60
 
6.0%
1 55
 
5.5%
8 46
 
4.6%
10 18
 
1.8%
9 18
 
1.8%
Other values (13) 20
 
2.0%

Length

2024-04-18T03:41:58.007424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 207
20.6%
4 169
16.8%
2 166
16.6%
5 147
14.7%
6 97
9.7%
7 60
 
6.0%
1 55
 
5.5%
8 46
 
4.6%
10 18
 
1.8%
9 18
 
1.8%
Other values (13) 20
 
2.0%

Unnamed: 8
Categorical

Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
1
308 
4
160 
6
157 
2
148 
8
75 
Other values (10)
155 

Length

Max length6
Median length1
Mean length1.0428714
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row차선수
3rd rowTFCLNE
4th row6
5th row1

Common Values

ValueCountFrequency (%)
1 308
30.7%
4 160
16.0%
6 157
15.7%
2 148
14.8%
8 75
 
7.5%
7 51
 
5.1%
5 37
 
3.7%
10 27
 
2.7%
3 20
 
2.0%
9 11
 
1.1%
Other values (5) 9
 
0.9%

Length

2024-04-18T03:41:58.098071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 308
30.7%
4 160
16.0%
6 157
15.7%
2 148
14.8%
8 75
 
7.5%
7 51
 
5.1%
5 37
 
3.7%
10 27
 
2.7%
3 20
 
2.0%
9 11
 
1.1%
Other values (5) 9
 
0.9%

Unnamed: 9
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
831 
유
169 
<NA>
 
1
버스차로유무
 
1
BUS_CARTRK_ENNC_SE
 
1

Length

Max length18
Median length1
Mean length1.0249252
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row버스차로유무
3rd rowBUS_CARTRK_ENNC_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
무 831
82.9%
유 169
 
16.8%
<NA> 1
 
0.1%
버스차로유무 1
 
0.1%
BUS_CARTRK_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:58.190804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:58.270975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 831
82.9%
유 169
 
16.8%
na 1
 
0.1%
버스차로유무 1
 
0.1%
bus_cartrk_ennc_se 1
 
0.1%

Unnamed: 10
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유
648 
무
352 
<NA>
 
1
중앙선여부
 
1
CTLN_AT_SE
 
1

Length

Max length10
Median length1
Mean length1.0159521
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row중앙선여부
3rd rowCTLN_AT_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
유 648
64.6%
무 352
35.1%
<NA> 1
 
0.1%
중앙선여부 1
 
0.1%
CTLN_AT_SE 1
 
0.1%

Length

2024-04-18T03:41:58.354084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:58.429988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 648
64.6%
무 352
35.1%
na 1
 
0.1%
중앙선여부 1
 
0.1%
ctln_at_se 1
 
0.1%

Unnamed: 11
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유
903 
무
97 
<NA>
 
1
장애물유무
 
1
OBSTC_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0189432
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row장애물유무
3rd rowOBSTC_ENNC_SE
4th row유
5th row유

Common Values

ValueCountFrequency (%)
유 903
90.0%
무 97
 
9.7%
<NA> 1
 
0.1%
장애물유무 1
 
0.1%
OBSTC_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:58.516132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:58.600556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 903
90.0%
무 97
 
9.7%
na 1
 
0.1%
장애물유무 1
 
0.1%
obstc_ennc_se 1
 
0.1%

Unnamed: 12
Categorical

Distinct20
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
가로수
283 
기둥(가로등등)
148 
불법주정차
132 
기타
114 
없음
102 
Other values (15)
224 

Length

Max length12
Median length8
Mean length4.6271186
Min length2

Unique

Unique6 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row장애물종류
3rd rowOBSTC_KND_CL
4th row가로수
5th row불법주정차

Common Values

ValueCountFrequency (%)
가로수 283
28.2%
기둥(가로등등) 148
14.8%
불법주정차 132
13.2%
기타 114
11.4%
없음 102
 
10.2%
상가고정장애물등 87
 
8.7%
노점상/가판대 59
 
5.9%
가로수보호대 25
 
2.5%
공중전화부스 11
 
1.1%
지하철계단 10
 
1.0%
Other values (10) 32
 
3.2%

Length

2024-04-18T03:41:58.704268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가로수 283
28.2%
기둥(가로등등 148
14.8%
불법주정차 132
13.2%
기타 114
11.4%
없음 102
 
10.2%
상가고정장애물등 87
 
8.7%
노점상/가판대 59
 
5.9%
가로수보호대 25
 
2.5%
공중전화부스 11
 
1.1%
지하철계단 10
 
1.0%
Other values (10) 32
 
3.2%

Unnamed: 13
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
보도전용
718 
자동차겸용
238 
보도차도겸용
 
44
<NA>
 
1
보행도로구분
 
1

Length

Max length12
Median length4
Mean length4.334995
Min length4

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row보행도로구분
3rd rowWALK_ROAD_SE
4th row보도차도겸용
5th row자동차겸용

Common Values

ValueCountFrequency (%)
보도전용 718
71.6%
자동차겸용 238
 
23.7%
보도차도겸용 44
 
4.4%
<NA> 1
 
0.1%
보행도로구분 1
 
0.1%
WALK_ROAD_SE 1
 
0.1%

Length

2024-04-18T03:41:58.828043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:58.921108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보도전용 718
71.6%
자동차겸용 238
 
23.7%
보도차도겸용 44
 
4.4%
na 1
 
0.1%
보행도로구분 1
 
0.1%
walk_road_se 1
 
0.1%

Unnamed: 14
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
613 
유
387 
<NA>
 
1
점자블록유무
 
1
BRLL_BLCK_ENNC_SE
 
1

Length

Max length17
Median length1
Mean length1.0239282
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row점자블록유무
3rd rowBRLL_BLCK_ENNC_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
무 613
61.1%
유 387
38.6%
<NA> 1
 
0.1%
점자블록유무 1
 
0.1%
BRLL_BLCK_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:59.022539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:59.102160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 613
61.1%
유 387
38.6%
na 1
 
0.1%
점자블록유무 1
 
0.1%
brll_blck_ennc_se 1
 
0.1%

Unnamed: 15
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
769 
유
231 
<NA>
 
1
경사로유무
 
1
SLPW__ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0189432
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row경사로유무
3rd rowSLPW__ENNC_SE
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 769
76.7%
유 231
 
23.0%
<NA> 1
 
0.1%
경사로유무 1
 
0.1%
SLPW__ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:59.185674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:59.263639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 769
76.7%
유 231
 
23.0%
na 1
 
0.1%
경사로유무 1
 
0.1%
slpw__ennc_se 1
 
0.1%

Unnamed: 16
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
792 
유
208 
<NA>
 
1
펜스유무
 
1
FENC_ENNC_SE
 
1

Length

Max length12
Median length1
Mean length1.0169492
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row펜스유무
3rd rowFENC_ENNC_SE
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 792
79.0%
유 208
 
20.7%
<NA> 1
 
0.1%
펜스유무 1
 
0.1%
FENC_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:59.348227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:59.425862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 792
79.0%
유 208
 
20.7%
na 1
 
0.1%
펜스유무 1
 
0.1%
fenc_ennc_se 1
 
0.1%

Unnamed: 17
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
576 
유
424 
<NA>
 
1
버스정류장유무
 
1
BUS_STOPG_IPLA_ENNC_SE
 
1

Length

Max length22
Median length1
Mean length1.0299103
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row버스정류장유무
3rd rowBUS_STOPG_IPLA_ENNC_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
무 576
57.4%
유 424
42.3%
<NA> 1
 
0.1%
버스정류장유무 1
 
0.1%
BUS_STOPG_IPLA_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:41:59.507529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:41:59.585282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 576
57.4%
유 424
42.3%
na 1
 
0.1%
버스정류장유무 1
 
0.1%
bus_stopg_ipla_ennc_se 1
 
0.1%

Unnamed: 18
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:41:59.698150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11.5
Mean length11.5
Min length6

Characters and Unicode

Total characters23
Distinct characters15
Distinct categories3 ?
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 (%)100.0%

Sample

1st row기타시설유무
2nd rowETC_FCLTY_ENNC_SE
ValueCountFrequency (%)
기타시설유무 1
50.0%
etc_fclty_ennc_se 1
50.0%
2024-04-18T03:41:59.935294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3
13.0%
C 3
13.0%
_ 3
13.0%
T 2
 
8.7%
N 2
 
8.7%
기 1
 
4.3%
타 1
 
4.3%
시 1
 
4.3%
설 1
 
4.3%
유 1
 
4.3%
Other values (5) 5
21.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 14
60.9%
Other Letter 6
26.1%
Connector Punctuation 3
 
13.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3
21.4%
C 3
21.4%
T 2
14.3%
N 2
14.3%
F 1
 
7.1%
L 1
 
7.1%
Y 1
 
7.1%
S 1
 
7.1%
Other Letter
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
시 1
16.7%
설 1
16.7%
유 1
16.7%
무 1
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
60.9%
Hangul 6
26.1%
Common 3
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3
21.4%
C 3
21.4%
T 2
14.3%
N 2
14.3%
F 1
 
7.1%
L 1
 
7.1%
Y 1
 
7.1%
S 1
 
7.1%
Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
시 1
16.7%
설 1
16.7%
유 1
16.7%
무 1
16.7%
Common
ValueCountFrequency (%)
_ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
73.9%
Hangul 6
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 3
17.6%
C 3
17.6%
_ 3
17.6%
T 2
11.8%
N 2
11.8%
F 1
 
5.9%
L 1
 
5.9%
Y 1
 
5.9%
S 1
 
5.9%
Hangul
ValueCountFrequency (%)
기 1
16.7%
타 1
16.7%
시 1
16.7%
설 1
16.7%
유 1
16.7%
무 1
16.7%

Unnamed: 19
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
무
785 
유
215 
<NA>
 
1
지하철유무
 
1
SUBWAY_ENNC_SE
 
1

Length

Max length14
Median length1
Mean length1.0199402
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row지하철유무
3rd rowSUBWAY_ENNC_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
무 785
78.3%
유 215
 
21.4%
<NA> 1
 
0.1%
지하철유무 1
 
0.1%
SUBWAY_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:42:00.043586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:00.126765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 785
78.3%
유 215
 
21.4%
na 1
 
0.1%
지하철유무 1
 
0.1%
subway_ennc_se 1
 
0.1%

Unnamed: 20
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유
630 
무
370 
<NA>
 
1
횡단보도유무
 
1
CRSLK_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0199402
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row횡단보도유무
3rd rowCRSLK_ENNC_SE
4th row유
5th row무

Common Values

ValueCountFrequency (%)
유 630
62.8%
무 370
36.9%
<NA> 1
 
0.1%
횡단보도유무 1
 
0.1%
CRSLK_ENNC_SE 1
 
0.1%

Length

2024-04-18T03:42:00.210495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:00.286535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 630
62.8%
무 370
36.9%
na 1
 
0.1%
횡단보도유무 1
 
0.1%
crslk_ennc_se 1
 
0.1%

Unnamed: 21
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:00.384588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8.5
Mean length8.5
Min length4

Characters and Unicode

Total characters17
Distinct characters14
Distinct categories3 ?
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 (%)100.0%

Sample

1st row보도형태
2nd rowFTPTH_STLE_CN
ValueCountFrequency (%)
보도형태 1
50.0%
ftpth_stle_cn 1
50.0%
2024-04-18T03:42:00.575908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 3
17.6%
_ 2
11.8%
보 1
 
5.9%
도 1
 
5.9%
형 1
 
5.9%
태 1
 
5.9%
F 1
 
5.9%
P 1
 
5.9%
H 1
 
5.9%
S 1
 
5.9%
Other values (4) 4
23.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 11
64.7%
Other Letter 4
 
23.5%
Connector Punctuation 2
 
11.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 3
27.3%
F 1
 
9.1%
P 1
 
9.1%
H 1
 
9.1%
S 1
 
9.1%
L 1
 
9.1%
E 1
 
9.1%
C 1
 
9.1%
N 1
 
9.1%
Other Letter
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
형 1
25.0%
태 1
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11
64.7%
Hangul 4
 
23.5%
Common 2
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 3
27.3%
F 1
 
9.1%
P 1
 
9.1%
H 1
 
9.1%
S 1
 
9.1%
L 1
 
9.1%
E 1
 
9.1%
C 1
 
9.1%
N 1
 
9.1%
Hangul
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
형 1
25.0%
태 1
25.0%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
76.5%
Hangul 4
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 3
23.1%
_ 2
15.4%
F 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
S 1
 
7.7%
L 1
 
7.7%
E 1
 
7.7%
C 1
 
7.7%
N 1
 
7.7%
Hangul
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
형 1
25.0%
태 1
25.0%

Unnamed: 22
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:00.695890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12
Min length7

Characters and Unicode

Total characters24
Distinct characters18
Distinct categories3 ?
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 (%)100.0%

Sample

1st row글로벌존지역명
2nd rowGLOBAL_ZN_AREA_NM
ValueCountFrequency (%)
글로벌존지역명 1
50.0%
global_zn_area_nm 1
50.0%
2024-04-18T03:42:00.900752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 3
 
12.5%
A 3
 
12.5%
N 2
 
8.3%
L 2
 
8.3%
글 1
 
4.2%
B 1
 
4.2%
E 1
 
4.2%
R 1
 
4.2%
Z 1
 
4.2%
O 1
 
4.2%
Other values (8) 8
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 14
58.3%
Other Letter 7
29.2%
Connector Punctuation 3
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3
21.4%
N 2
14.3%
L 2
14.3%
B 1
 
7.1%
E 1
 
7.1%
R 1
 
7.1%
Z 1
 
7.1%
O 1
 
7.1%
G 1
 
7.1%
M 1
 
7.1%
Other Letter
ValueCountFrequency (%)
글 1
14.3%
로 1
14.3%
명 1
14.3%
역 1
14.3%
지 1
14.3%
존 1
14.3%
벌 1
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
58.3%
Hangul 7
29.2%
Common 3
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3
21.4%
N 2
14.3%
L 2
14.3%
B 1
 
7.1%
E 1
 
7.1%
R 1
 
7.1%
Z 1
 
7.1%
O 1
 
7.1%
G 1
 
7.1%
M 1
 
7.1%
Hangul
ValueCountFrequency (%)
글 1
14.3%
로 1
14.3%
명 1
14.3%
역 1
14.3%
지 1
14.3%
존 1
14.3%
벌 1
14.3%
Common
ValueCountFrequency (%)
_ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
70.8%
Hangul 7
29.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 3
17.6%
A 3
17.6%
N 2
11.8%
L 2
11.8%
B 1
 
5.9%
E 1
 
5.9%
R 1
 
5.9%
Z 1
 
5.9%
O 1
 
5.9%
G 1
 
5.9%
Hangul
ValueCountFrequency (%)
글 1
14.3%
로 1
14.3%
명 1
14.3%
역 1
14.3%
지 1
14.3%
존 1
14.3%
벌 1
14.3%

Unnamed: 23
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:01.017127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9.5
Mean length9.5
Min length5

Characters and Unicode

Total characters19
Distinct characters14
Distinct categories3 ?
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 (%)100.0%

Sample

1st row주거지역명
2nd rowRESIDE_AREA_NM
ValueCountFrequency (%)
주거지역명 1
50.0%
reside_area_nm 1
50.0%
2024-04-18T03:42:01.218316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3
15.8%
R 2
10.5%
_ 2
10.5%
A 2
10.5%
주 1
 
5.3%
거 1
 
5.3%
지 1
 
5.3%
역 1
 
5.3%
명 1
 
5.3%
S 1
 
5.3%
Other values (4) 4
21.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12
63.2%
Other Letter 5
26.3%
Connector Punctuation 2
 
10.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3
25.0%
R 2
16.7%
A 2
16.7%
S 1
 
8.3%
I 1
 
8.3%
D 1
 
8.3%
N 1
 
8.3%
M 1
 
8.3%
Other Letter
ValueCountFrequency (%)
주 1
20.0%
거 1
20.0%
지 1
20.0%
역 1
20.0%
명 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
63.2%
Hangul 5
26.3%
Common 2
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3
25.0%
R 2
16.7%
A 2
16.7%
S 1
 
8.3%
I 1
 
8.3%
D 1
 
8.3%
N 1
 
8.3%
M 1
 
8.3%
Hangul
ValueCountFrequency (%)
주 1
20.0%
거 1
20.0%
지 1
20.0%
역 1
20.0%
명 1
20.0%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
73.7%
Hangul 5
 
26.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 3
21.4%
R 2
14.3%
_ 2
14.3%
A 2
14.3%
S 1
 
7.1%
I 1
 
7.1%
D 1
 
7.1%
N 1
 
7.1%
M 1
 
7.1%
Hangul
ValueCountFrequency (%)
주 1
20.0%
거 1
20.0%
지 1
20.0%
역 1
20.0%
명 1
20.0%

Unnamed: 24
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:01.554776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9.5
Mean length9.5
Min length5

Characters and Unicode

Total characters19
Distinct characters13
Distinct categories3 ?
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 (%)100.0%

Sample

1st row지역중심명
2nd rowAREA_CENTER_NM
ValueCountFrequency (%)
지역중심명 1
50.0%
area_center_nm 1
50.0%
2024-04-18T03:42:01.786553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3
15.8%
A 2
10.5%
R 2
10.5%
_ 2
10.5%
N 2
10.5%
지 1
 
5.3%
역 1
 
5.3%
중 1
 
5.3%
심 1
 
5.3%
명 1
 
5.3%
Other values (3) 3
15.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12
63.2%
Other Letter 5
26.3%
Connector Punctuation 2
 
10.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3
25.0%
A 2
16.7%
R 2
16.7%
N 2
16.7%
C 1
 
8.3%
T 1
 
8.3%
M 1
 
8.3%
Other Letter
ValueCountFrequency (%)
지 1
20.0%
역 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
63.2%
Hangul 5
26.3%
Common 2
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3
25.0%
A 2
16.7%
R 2
16.7%
N 2
16.7%
C 1
 
8.3%
T 1
 
8.3%
M 1
 
8.3%
Hangul
ValueCountFrequency (%)
지 1
20.0%
역 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
73.7%
Hangul 5
 
26.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 3
21.4%
A 2
14.3%
R 2
14.3%
_ 2
14.3%
N 2
14.3%
C 1
 
7.1%
T 1
 
7.1%
M 1
 
7.1%
Hangul
ValueCountFrequency (%)
지 1
20.0%
역 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%

Unnamed: 25
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:01.910949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length14
Min length7

Characters and Unicode

Total characters28
Distinct characters18
Distinct categories3 ?
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 (%)100.0%

Sample

1st row지역중심상세명
2nd rowAREA_CENTER_DETAIL_NM
ValueCountFrequency (%)
지역중심상세명 1
50.0%
area_center_detail_nm 1
50.0%
2024-04-18T03:42:02.120981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 4
14.3%
_ 3
 
10.7%
A 3
 
10.7%
T 2
 
7.1%
N 2
 
7.1%
R 2
 
7.1%
L 1
 
3.6%
I 1
 
3.6%
D 1
 
3.6%
C 1
 
3.6%
Other values (8) 8
28.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18
64.3%
Other Letter 7
 
25.0%
Connector Punctuation 3
 
10.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 4
22.2%
A 3
16.7%
T 2
11.1%
N 2
11.1%
R 2
11.1%
L 1
 
5.6%
I 1
 
5.6%
D 1
 
5.6%
C 1
 
5.6%
M 1
 
5.6%
Other Letter
ValueCountFrequency (%)
지 1
14.3%
역 1
14.3%
명 1
14.3%
세 1
14.3%
상 1
14.3%
심 1
14.3%
중 1
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18
64.3%
Hangul 7
 
25.0%
Common 3
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 4
22.2%
A 3
16.7%
T 2
11.1%
N 2
11.1%
R 2
11.1%
L 1
 
5.6%
I 1
 
5.6%
D 1
 
5.6%
C 1
 
5.6%
M 1
 
5.6%
Hangul
ValueCountFrequency (%)
지 1
14.3%
역 1
14.3%
명 1
14.3%
세 1
14.3%
상 1
14.3%
심 1
14.3%
중 1
14.3%
Common
ValueCountFrequency (%)
_ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
75.0%
Hangul 7
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 4
19.0%
_ 3
14.3%
A 3
14.3%
T 2
9.5%
N 2
9.5%
R 2
9.5%
L 1
 
4.8%
I 1
 
4.8%
D 1
 
4.8%
C 1
 
4.8%
Hangul
ValueCountFrequency (%)
지 1
14.3%
역 1
14.3%
명 1
14.3%
세 1
14.3%
상 1
14.3%
심 1
14.3%
중 1
14.3%

Unnamed: 26
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:02.232638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length10
Min length5

Characters and Unicode

Total characters20
Distinct characters14
Distinct categories3 ?
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 (%)100.0%

Sample

1st row지구중심명
2nd rowDSTRC_CENTER_NM
ValueCountFrequency (%)
지구중심명 1
50.0%
dstrc_center_nm 1
50.0%
2024-04-18T03:42:02.430060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
10.0%
R 2
10.0%
C 2
10.0%
_ 2
10.0%
E 2
10.0%
N 2
10.0%
지 1
 
5.0%
구 1
 
5.0%
중 1
 
5.0%
심 1
 
5.0%
Other values (4) 4
20.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 13
65.0%
Other Letter 5
 
25.0%
Connector Punctuation 2
 
10.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 2
15.4%
R 2
15.4%
C 2
15.4%
E 2
15.4%
N 2
15.4%
D 1
7.7%
S 1
7.7%
M 1
7.7%
Other Letter
ValueCountFrequency (%)
지 1
20.0%
구 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
65.0%
Hangul 5
 
25.0%
Common 2
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
15.4%
R 2
15.4%
C 2
15.4%
E 2
15.4%
N 2
15.4%
D 1
7.7%
S 1
7.7%
M 1
7.7%
Hangul
ValueCountFrequency (%)
지 1
20.0%
구 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
75.0%
Hangul 5
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
13.3%
R 2
13.3%
C 2
13.3%
_ 2
13.3%
E 2
13.3%
N 2
13.3%
D 1
6.7%
S 1
6.7%
M 1
6.7%
Hangul
ValueCountFrequency (%)
지 1
20.0%
구 1
20.0%
중 1
20.0%
심 1
20.0%
명 1
20.0%

Unnamed: 27
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:02.546222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13.5
Mean length13.5
Min length8

Characters and Unicode

Total characters27
Distinct characters19
Distinct categories3 ?
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 (%)100.0%

Sample

1st row지구중심상세내용
2nd rowDSTRC_CENTER_DETAIL
ValueCountFrequency (%)
지구중심상세내용 1
50.0%
dstrc_center_detail 1
50.0%
2024-04-18T03:42:02.763134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 3
 
11.1%
E 3
 
11.1%
_ 2
 
7.4%
C 2
 
7.4%
D 2
 
7.4%
R 2
 
7.4%
지 1
 
3.7%
I 1
 
3.7%
A 1
 
3.7%
N 1
 
3.7%
Other values (9) 9
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 17
63.0%
Other Letter 8
29.6%
Connector Punctuation 2
 
7.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 3
17.6%
E 3
17.6%
C 2
11.8%
D 2
11.8%
R 2
11.8%
I 1
 
5.9%
A 1
 
5.9%
N 1
 
5.9%
S 1
 
5.9%
L 1
 
5.9%
Other Letter
ValueCountFrequency (%)
지 1
12.5%
구 1
12.5%
용 1
12.5%
내 1
12.5%
세 1
12.5%
상 1
12.5%
심 1
12.5%
중 1
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17
63.0%
Hangul 8
29.6%
Common 2
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 3
17.6%
E 3
17.6%
C 2
11.8%
D 2
11.8%
R 2
11.8%
I 1
 
5.9%
A 1
 
5.9%
N 1
 
5.9%
S 1
 
5.9%
L 1
 
5.9%
Hangul
ValueCountFrequency (%)
지 1
12.5%
구 1
12.5%
용 1
12.5%
내 1
12.5%
세 1
12.5%
상 1
12.5%
심 1
12.5%
중 1
12.5%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
70.4%
Hangul 8
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 3
15.8%
E 3
15.8%
_ 2
10.5%
C 2
10.5%
D 2
10.5%
R 2
10.5%
I 1
 
5.3%
A 1
 
5.3%
N 1
 
5.3%
S 1
 
5.3%
Hangul
ValueCountFrequency (%)
지 1
12.5%
구 1
12.5%
용 1
12.5%
내 1
12.5%
세 1
12.5%
상 1
12.5%
심 1
12.5%
중 1
12.5%

Unnamed: 28
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:02.884753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14.5
Mean length14.5
Min length8

Characters and Unicode

Total characters29
Distinct characters18
Distinct categories3 ?
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 (%)100.0%

Sample

1st row도심부도심지역명
2nd rowCDCT_SUB_CDCT_AREA_NM
ValueCountFrequency (%)
도심부도심지역명 1
50.0%
cdct_sub_cdct_area_nm 1
50.0%
2024-04-18T03:42:03.126374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 4
13.8%
C 4
13.8%
A 2
 
6.9%
심 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
도 2
 
6.9%
명 1
 
3.4%
역 1
 
3.4%
지 1
 
3.4%
Other values (8) 8
27.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 17
58.6%
Other Letter 8
27.6%
Connector Punctuation 4
 
13.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
23.5%
A 2
11.8%
T 2
11.8%
D 2
11.8%
S 1
 
5.9%
U 1
 
5.9%
B 1
 
5.9%
R 1
 
5.9%
E 1
 
5.9%
N 1
 
5.9%
Other Letter
ValueCountFrequency (%)
심 2
25.0%
도 2
25.0%
명 1
12.5%
역 1
12.5%
지 1
12.5%
부 1
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17
58.6%
Hangul 8
27.6%
Common 4
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
23.5%
A 2
11.8%
T 2
11.8%
D 2
11.8%
S 1
 
5.9%
U 1
 
5.9%
B 1
 
5.9%
R 1
 
5.9%
E 1
 
5.9%
N 1
 
5.9%
Hangul
ValueCountFrequency (%)
심 2
25.0%
도 2
25.0%
명 1
12.5%
역 1
12.5%
지 1
12.5%
부 1
12.5%
Common
ValueCountFrequency (%)
_ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
72.4%
Hangul 8
 
27.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 4
19.0%
C 4
19.0%
A 2
9.5%
T 2
9.5%
D 2
9.5%
S 1
 
4.8%
U 1
 
4.8%
B 1
 
4.8%
R 1
 
4.8%
E 1
 
4.8%
Other values (2) 2
9.5%
Hangul
ValueCountFrequency (%)
심 2
25.0%
도 2
25.0%
명 1
12.5%
역 1
12.5%
지 1
12.5%
부 1
12.5%

Unnamed: 29
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:03.226049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6
Min length4

Characters and Unicode

Total characters12
Distinct characters11
Distinct categories3 ?
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 (%)100.0%

Sample

1st row용도구분
2nd rowPRPOS_NM
ValueCountFrequency (%)
용도구분 1
50.0%
prpos_nm 1
50.0%
2024-04-18T03:42:03.454874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 2
16.7%
용 1
8.3%
도 1
8.3%
구 1
8.3%
분 1
8.3%
R 1
8.3%
O 1
8.3%
S 1
8.3%
_ 1
8.3%
N 1
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7
58.3%
Other Letter 4
33.3%
Connector Punctuation 1
 
8.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 2
28.6%
R 1
14.3%
O 1
14.3%
S 1
14.3%
N 1
14.3%
M 1
14.3%
Other Letter
ValueCountFrequency (%)
용 1
25.0%
도 1
25.0%
구 1
25.0%
분 1
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7
58.3%
Hangul 4
33.3%
Common 1
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 2
28.6%
R 1
14.3%
O 1
14.3%
S 1
14.3%
N 1
14.3%
M 1
14.3%
Hangul
ValueCountFrequency (%)
용 1
25.0%
도 1
25.0%
구 1
25.0%
분 1
25.0%
Common
ValueCountFrequency (%)
_ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
66.7%
Hangul 4
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 2
25.0%
R 1
12.5%
O 1
12.5%
S 1
12.5%
_ 1
12.5%
N 1
12.5%
M 1
12.5%
Hangul
ValueCountFrequency (%)
용 1
25.0%
도 1
25.0%
구 1
25.0%
분 1
25.0%

Unnamed: 30
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:03.560993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9
Min length6

Characters and Unicode

Total characters18
Distinct characters14
Distinct categories3 ?
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 (%)100.0%

Sample

1st row거주유형구분
2nd rowRESIDE_TY_SE
ValueCountFrequency (%)
거주유형구분 1
50.0%
reside_ty_se 1
50.0%
2024-04-18T03:42:03.755904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3
16.7%
S 2
11.1%
_ 2
11.1%
거 1
 
5.6%
주 1
 
5.6%
유 1
 
5.6%
형 1
 
5.6%
구 1
 
5.6%
분 1
 
5.6%
R 1
 
5.6%
Other values (4) 4
22.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10
55.6%
Other Letter 6
33.3%
Connector Punctuation 2
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3
30.0%
S 2
20.0%
R 1
 
10.0%
I 1
 
10.0%
D 1
 
10.0%
T 1
 
10.0%
Y 1
 
10.0%
Other Letter
ValueCountFrequency (%)
거 1
16.7%
주 1
16.7%
유 1
16.7%
형 1
16.7%
구 1
16.7%
분 1
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
55.6%
Hangul 6
33.3%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3
30.0%
S 2
20.0%
R 1
 
10.0%
I 1
 
10.0%
D 1
 
10.0%
T 1
 
10.0%
Y 1
 
10.0%
Hangul
ValueCountFrequency (%)
거 1
16.7%
주 1
16.7%
유 1
16.7%
형 1
16.7%
구 1
16.7%
분 1
16.7%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
66.7%
Hangul 6
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 3
25.0%
S 2
16.7%
_ 2
16.7%
R 1
 
8.3%
I 1
 
8.3%
D 1
 
8.3%
T 1
 
8.3%
Y 1
 
8.3%
Hangul
ValueCountFrequency (%)
거 1
16.7%
주 1
16.7%
유 1
16.7%
형 1
16.7%
구 1
16.7%
분 1
16.7%

Unnamed: 31
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1001
Missing (%)99.8%
Memory size8.0 KiB
2024-04-18T03:42:03.860454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7
Min length5

Characters and Unicode

Total characters14
Distinct characters12
Distinct categories3 ?
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 (%)100.0%

Sample

1st row입지유형명
2nd rowLCT_TY_NM
ValueCountFrequency (%)
입지유형명 1
50.0%
lct_ty_nm 1
50.0%
2024-04-18T03:42:04.071477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
14.3%
_ 2
14.3%
입 1
7.1%
지 1
7.1%
유 1
7.1%
형 1
7.1%
명 1
7.1%
L 1
7.1%
C 1
7.1%
Y 1
7.1%
Other values (2) 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7
50.0%
Other Letter 5
35.7%
Connector Punctuation 2
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 2
28.6%
L 1
14.3%
C 1
14.3%
Y 1
14.3%
N 1
14.3%
M 1
14.3%
Other Letter
ValueCountFrequency (%)
입 1
20.0%
지 1
20.0%
유 1
20.0%
형 1
20.0%
명 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7
50.0%
Hangul 5
35.7%
Common 2
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
28.6%
L 1
14.3%
C 1
14.3%
Y 1
14.3%
N 1
14.3%
M 1
14.3%
Hangul
ValueCountFrequency (%)
입 1
20.0%
지 1
20.0%
유 1
20.0%
형 1
20.0%
명 1
20.0%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
64.3%
Hangul 5
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
22.2%
_ 2
22.2%
L 1
11.1%
C 1
11.1%
Y 1
11.1%
N 1
11.1%
M 1
11.1%
Hangul
ValueCountFrequency (%)
입 1
20.0%
지 1
20.0%
유 1
20.0%
형 1
20.0%
명 1
20.0%

Unnamed: 32
Text

MISSING 

Distinct989
Distinct (%)100.0%
Missing14
Missing (%)1.4%
Memory size8.0 KiB
2024-04-18T03:42:04.254179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.869565
Min length3

Characters and Unicode

Total characters11739
Distinct characters19
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

Unique989 ?
Unique (%)100.0%

Sample

1st rowX좌표
2nd rowXCRD_LC
3rd row200202.62257
4th row198887.82848
5th row198688.03274
ValueCountFrequency (%)
197791.50396 1
 
0.1%
192177.96638 1
 
0.1%
189824.34376 1
 
0.1%
189802.87668 1
 
0.1%
189866.81527 1
 
0.1%
189977.14904 1
 
0.1%
189908.06525 1
 
0.1%
190216.66953 1
 
0.1%
190234.34789 1
 
0.1%
190031.60737 1
 
0.1%
Other values (979) 979
99.0%
2024-04-18T03:42:04.541211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1415
12.1%
1 1380
11.8%
9 1325
11.3%
0 1210
10.3%
8 1019
8.7%
. 987
8.4%
6 903
7.7%
7 888
7.6%
5 878
7.5%
3 874
7.4%
Other values (9) 860
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10742
91.5%
Other Punctuation 987
 
8.4%
Uppercase Letter 7
 
0.1%
Other Letter 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1415
13.2%
1 1380
12.8%
9 1325
12.3%
0 1210
11.3%
8 1019
9.5%
6 903
8.4%
7 888
8.3%
5 878
8.2%
3 874
8.1%
4 850
7.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
X 2
28.6%
R 1
14.3%
D 1
14.3%
L 1
14.3%
Other Letter
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 987
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11730
99.9%
Latin 7
 
0.1%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1415
12.1%
1 1380
11.8%
9 1325
11.3%
0 1210
10.3%
8 1019
8.7%
. 987
8.4%
6 903
7.7%
7 888
7.6%
5 878
7.5%
3 874
7.5%
Other values (2) 851
7.3%
Latin
ValueCountFrequency (%)
C 2
28.6%
X 2
28.6%
R 1
14.3%
D 1
14.3%
L 1
14.3%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11737
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1415
12.1%
1 1380
11.8%
9 1325
11.3%
0 1210
10.3%
8 1019
8.7%
. 987
8.4%
6 903
7.7%
7 888
7.6%
5 878
7.5%
3 874
7.4%
Other values (7) 858
7.3%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Unnamed: 33
Text

MISSING 

Distinct989
Distinct (%)100.0%
Missing14
Missing (%)1.4%
Memory size8.0 KiB
2024-04-18T03:42:04.754385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.892821
Min length3

Characters and Unicode

Total characters11762
Distinct characters19
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

Unique989 ?
Unique (%)100.0%

Sample

1st rowY좌표
2nd rowYCRD_LC
3rd row453589.66617
4th row452154.59925
5th row452134.47214
ValueCountFrequency (%)
452555.95179 1
 
0.1%
446096.9831 1
 
0.1%
443230.88204 1
 
0.1%
443180.65252 1
 
0.1%
442998.32625 1
 
0.1%
443155.50293 1
 
0.1%
442880.76089 1
 
0.1%
443013.04281 1
 
0.1%
442949.22863 1
 
0.1%
442830.07157 1
 
0.1%
Other values (979) 979
99.0%
2024-04-18T03:42:05.094385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2311
19.6%
5 1358
11.5%
. 987
8.4%
3 962
8.2%
2 931
7.9%
8 922
 
7.8%
7 894
 
7.6%
1 891
 
7.6%
6 891
 
7.6%
9 817
 
6.9%
Other values (9) 798
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10765
91.5%
Other Punctuation 987
 
8.4%
Uppercase Letter 7
 
0.1%
Other Letter 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2311
21.5%
5 1358
12.6%
3 962
8.9%
2 931
8.6%
8 922
 
8.6%
7 894
 
8.3%
1 891
 
8.3%
6 891
 
8.3%
9 817
 
7.6%
0 788
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
Y 2
28.6%
C 2
28.6%
R 1
14.3%
D 1
14.3%
L 1
14.3%
Other Letter
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 987
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11753
99.9%
Latin 7
 
0.1%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2311
19.7%
5 1358
11.6%
. 987
8.4%
3 962
8.2%
2 931
7.9%
8 922
 
7.8%
7 894
 
7.6%
1 891
 
7.6%
6 891
 
7.6%
9 817
 
7.0%
Other values (2) 789
 
6.7%
Latin
ValueCountFrequency (%)
Y 2
28.6%
C 2
28.6%
R 1
14.3%
D 1
14.3%
L 1
14.3%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11760
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2311
19.7%
5 1358
11.5%
. 987
8.4%
3 962
8.2%
2 931
7.9%
8 922
 
7.8%
7 894
 
7.6%
1 891
 
7.6%
6 891
 
7.6%
9 817
 
6.9%
Other values (7) 796
 
6.8%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Unnamed: 34
Text

MISSING 

Distinct787
Distinct (%)79.6%
Missing14
Missing (%)1.4%
Memory size8.0 KiB
2024-04-18T03:42:05.290219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.986855
Min length5

Characters and Unicode

Total characters12844
Distinct characters22
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

Unique669 ?
Unique (%)67.6%

Sample

1st row집계구코드
2nd rowSM_GU_CD
3rd row1101064020001
4th row1101061040001
5th row1101061040001
ValueCountFrequency (%)
1102055060001 20
 
2.0%
1101061040001 13
 
1.3%
1102052020001 7
 
0.7%
1119054050001 6
 
0.6%
1113075020002 6
 
0.6%
1101054010002 5
 
0.5%
1102054070001 5
 
0.5%
1101061030002 5
 
0.5%
1102052010001 5
 
0.5%
1101061020001 4
 
0.4%
Other values (777) 913
92.3%
2024-04-18T03:42:05.592123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5242
40.8%
1 3403
26.5%
2 1052
 
8.2%
5 710
 
5.5%
6 585
 
4.6%
3 514
 
4.0%
7 462
 
3.6%
4 443
 
3.4%
8 211
 
1.6%
9 209
 
1.6%
Other values (12) 13
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12831
99.9%
Uppercase Letter 6
 
< 0.1%
Other Letter 5
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5242
40.9%
1 3403
26.5%
2 1052
 
8.2%
5 710
 
5.5%
6 585
 
4.6%
3 514
 
4.0%
7 462
 
3.6%
4 443
 
3.5%
8 211
 
1.6%
9 209
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
M 1
16.7%
C 1
16.7%
U 1
16.7%
G 1
16.7%
S 1
16.7%
D 1
16.7%
Other Letter
ValueCountFrequency (%)
계 1
20.0%
드 1
20.0%
코 1
20.0%
구 1
20.0%
집 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12833
99.9%
Latin 6
 
< 0.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5242
40.8%
1 3403
26.5%
2 1052
 
8.2%
5 710
 
5.5%
6 585
 
4.6%
3 514
 
4.0%
7 462
 
3.6%
4 443
 
3.5%
8 211
 
1.6%
9 209
 
1.6%
Latin
ValueCountFrequency (%)
M 1
16.7%
C 1
16.7%
U 1
16.7%
G 1
16.7%
S 1
16.7%
D 1
16.7%
Hangul
ValueCountFrequency (%)
계 1
20.0%
드 1
20.0%
코 1
20.0%
구 1
20.0%
집 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12839
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5242
40.8%
1 3403
26.5%
2 1052
 
8.2%
5 710
 
5.5%
6 585
 
4.6%
3 514
 
4.0%
7 462
 
3.6%
4 443
 
3.5%
8 211
 
1.6%
9 209
 
1.6%
Other values (7) 8
 
0.1%
Hangul
ValueCountFrequency (%)
계 1
20.0%
드 1
20.0%
코 1
20.0%
구 1
20.0%
집 1
20.0%

Unnamed: 35
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2013
1000 
<NA>
 
1
년도
 
1
YEAR
 
1

Length

Max length4
Median length4
Mean length3.998006
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
2013 1000
99.7%
<NA> 1
 
0.1%
년도 1
 
0.1%
YEAR 1
 
0.1%

Length

2024-04-18T03:42:05.708139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:05.789917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 1000
99.7%
na 1
 
0.1%
년도 1
 
0.1%
year 1
 
0.1%

Unnamed: 36
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
본조사
1000 
<NA>
 
1
조사구분
 
1
EXAMIN_CLS
 
1

Length

Max length10
Median length3
Mean length3.0089731
Min length3

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row조사구분
3rd rowEXAMIN_CLS
4th row본조사
5th row본조사

Common Values

ValueCountFrequency (%)
본조사 1000
99.7%
<NA> 1
 
0.1%
조사구분 1
 
0.1%
EXAMIN_CLS 1
 
0.1%

Length

2024-04-18T03:42:05.879488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:05.982726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본조사 1000
99.7%
na 1
 
0.1%
조사구분 1
 
0.1%
examin_cls 1
 
0.1%

Sample

유동인구_조사지점정보_2013Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34Unnamed: 35Unnamed: 36
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1조사지점코드조사지점명구코드동코드주번지부번지도로명보도너비차선수버스차로유무중앙선여부장애물유무장애물종류보행도로구분점자블록유무경사로유무펜스유무버스정류장유무기타시설유무지하철유무횡단보도유무보도형태글로벌존지역명주거지역명지역중심명지역중심상세명지구중심명지구중심상세내용도심부도심지역명용도구분거주유형구분입지유형명X좌표Y좌표집계구코드년도조사구분
2EXAMIN_SPOT_CDEXAMIN_SPOT_NMGU_CDDONG_CDBUNJIBUBUNROAD_NMFTPTH_BTTFCLNEBUS_CARTRK_ENNC_SECTLN_AT_SEOBSTC_ENNC_SEOBSTC_KND_CLWALK_ROAD_SEBRLL_BLCK_ENNC_SESLPW__ENNC_SEFENC_ENNC_SEBUS_STOPG_IPLA_ENNC_SEETC_FCLTY_ENNC_SESUBWAY_ENNC_SECRSLK_ENNC_SEFTPTH_STLE_CNGLOBAL_ZN_AREA_NMRESIDE_AREA_NMAREA_CENTER_NMAREA_CENTER_DETAIL_NMDSTRC_CENTER_NMDSTRC_CENTER_DETAILCDCT_SUB_CDCT_AREA_NMPRPOS_NMRESIDE_TY_SELCT_TY_NMXCRD_LCYCRD_LCSM_GU_CDYEAREXAMIN_CLS
301-029KFC110101101064127대학로 12046유유유가로수보도차도겸용유무무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>200202.62257453589.6661711010640200012013본조사
401-033오복영양치킨11010110106151종로구 종로 16길 1261무무유불법주정차자동차겸용무무무무<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198887.82848452154.5992511010610400012013본조사
501-035영안빌딩(미샤옆)110101101061841종로구 종로 7471무무유노점상/가판대보도전용무무무무<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198688.03274452134.4721411010610400012013본조사
601-036파리바게트시그너치110101101061704종로 3488무유유기타보도전용무무유유<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198342.17129452307.8001111010610300022013본조사
701-041우리은행재동지점1101011010601115율곡로 5746무유유가로수보도전용유무무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198723.55829453024.8942411010600100012013본조사
801-045종로경찰서민원봉사실1101011010549018율곡로 4686무유유기타보도전용유무무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198652.79698453002.1399811010540100012013본조사
901-051한솔약국110101101053260사직로 10747무유유가로수보도전용무무무유<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>197424.31351452948.0623211010530100032013본조사
유동인구_조사지점정보_2013Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34Unnamed: 35Unnamed: 36
99325-422주양쇼핑식품관입구112501125054480고덕로62길 5541무유유가로수보도전용무무무무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>213525.32853450318.2094111250540100032013본조사
99425-427채플린노래연습장1125011250725004올림픽로 79054무유유기둥(가로등등)보도전용무무유무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211351.2532450215.0759711250720100172013본조사
99525-450티:맑은(커피,한방차)1125011250744115양재대로 110길 351무유유불법주정차자동차겸용무무무무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212337.90538448468.4327811250740500092013본조사
99625-452삼성타운A동1125011250744108천호대로 191길 6451무무유불법주정차자동차겸용무무무무<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212478.41145448515.9305311250740500102013본조사
99725-458길동자치회관(길동파출소)1125011250742286천호대로 187길 671무무유불법주정차자동차겸용무무무무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212588.20485448348.0846211250740500072013본조사
99825-480사바사바치킨호프집1125011250744400양재대로 144878무유유기타보도전용유무무무<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212311.68253448395.1481711250740500162013본조사
99925-814세경주택입구1125011250661800천호대로 168길31무무유불법주정차보도전용무유무무<NA>유무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211665.36477448420.2779711250660200032013본조사
100025-818명품아구해물찜1125011250673785천호대로 176길 1981무무무없음자동차겸용무무무무<NA>무무<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212010.33046448237.9316611250670100092013본조사
100125-820NH개발1125011250655530올림픽로 48길 731무무유불법주정차자동차겸용무무무무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>210645.11157447778.3814511250650200012013본조사
100225-822부산오뎅1125011250655562성내로 6길2072무유유가로수보도전용유무유무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>210850.50788447742.5624111250650200012013본조사