Overview

Dataset statistics

Number of variables37
Number of observations1108
Missing cells13604
Missing cells (%)33.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory320.4 KiB
Average record size in memory296.1 B

Variable types

Text20
Categorical15
Unsupported2

Dataset

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

Alerts

Unnamed: 9 is highly imbalanced (70.3%)Imbalance
Unnamed: 10 is highly imbalanced (67.0%)Imbalance
Unnamed: 11 is highly imbalanced (83.7%)Imbalance
Unnamed: 13 is highly imbalanced (60.2%)Imbalance
Unnamed: 14 is highly imbalanced (55.7%)Imbalance
Unnamed: 15 is highly imbalanced (63.6%)Imbalance
Unnamed: 16 is highly imbalanced (63.7%)Imbalance
Unnamed: 17 is highly imbalanced (56.2%)Imbalance
Unnamed: 19 is highly imbalanced (68.7%)Imbalance
Unnamed: 20 is highly imbalanced (62.1%)Imbalance
Unnamed: 35 is highly imbalanced (98.4%)Imbalance
Unnamed: 36 is highly imbalanced (98.4%)Imbalance
Unnamed: 5 has 235 (21.2%) missing valuesMissing
Unnamed: 6 has 89 (8.0%) missing valuesMissing
Unnamed: 18 has 1106 (99.8%) missing valuesMissing
Unnamed: 21 has 1106 (99.8%) missing valuesMissing
Unnamed: 22 has 1106 (99.8%) missing valuesMissing
Unnamed: 23 has 1106 (99.8%) missing valuesMissing
Unnamed: 24 has 1106 (99.8%) missing valuesMissing
Unnamed: 25 has 1106 (99.8%) missing valuesMissing
Unnamed: 26 has 1106 (99.8%) missing valuesMissing
Unnamed: 27 has 1106 (99.8%) missing valuesMissing
Unnamed: 28 has 1106 (99.8%) missing valuesMissing
Unnamed: 29 has 1106 (99.8%) missing valuesMissing
Unnamed: 30 has 1106 (99.8%) missing valuesMissing
Unnamed: 31 has 1106 (99.8%) missing valuesMissing
Unnamed: 32 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 33 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-09-17 11:03:51.249590
Analysis finished2023-09-17 11:03:52.904745
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동인구_조사지점정보_2014
Text

Distinct1107
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:03:53.340473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.1897019
Min length6

Characters and Unicode

Total characters6852
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

Unique1107 ?
Unique (%)100.0%

Sample

1st row조사지점코드
2nd rowEXAMIN_SPOT_CD
3rd row01-001
4th row01-002
5th row01-004
ValueCountFrequency (%)
01-012 1
 
0.1%
18-001 1
 
0.1%
17-3052 1
 
0.1%
17-3070 1
 
0.1%
17-3082 1
 
0.1%
17-3090 1
 
0.1%
17-3117 1
 
0.1%
17-258 1
 
0.1%
18-003 1
 
0.1%
17-252 1
 
0.1%
Other values (1097) 1097
99.1%
2023-09-17T20:03:54.144571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1553
22.7%
- 1105
16.1%
1 1076
15.7%
2 960
14.0%
3 447
 
6.5%
4 400
 
5.8%
5 352
 
5.1%
6 267
 
3.9%
7 246
 
3.6%
9 224
 
3.3%
Other values (20) 222
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5727
83.6%
Dash Punctuation 1105
 
16.1%
Uppercase Letter 12
 
0.2%
Other Letter 6
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 1
8.3%
I 1
8.3%
E 1
8.3%
X 1
8.3%
D 1
8.3%
C 1
8.3%
T 1
8.3%
O 1
8.3%
P 1
8.3%
S 1
8.3%
Other values (2) 2
16.7%
Decimal Number
ValueCountFrequency (%)
0 1553
27.1%
1 1076
18.8%
2 960
16.8%
3 447
 
7.8%
4 400
 
7.0%
5 352
 
6.1%
6 267
 
4.7%
7 246
 
4.3%
9 224
 
3.9%
8 202
 
3.5%
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 (%)
- 1105
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6834
99.7%
Latin 12
 
0.2%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1553
22.7%
- 1105
16.2%
1 1076
15.7%
2 960
14.0%
3 447
 
6.5%
4 400
 
5.9%
5 352
 
5.2%
6 267
 
3.9%
7 246
 
3.6%
9 224
 
3.3%
Other values (2) 204
 
3.0%
Latin
ValueCountFrequency (%)
M 1
8.3%
I 1
8.3%
E 1
8.3%
X 1
8.3%
D 1
8.3%
C 1
8.3%
T 1
8.3%
O 1
8.3%
P 1
8.3%
S 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 6846
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1553
22.7%
- 1105
16.1%
1 1076
15.7%
2 960
14.0%
3 447
 
6.5%
4 400
 
5.8%
5 352
 
5.1%
6 267
 
3.9%
7 246
 
3.6%
9 224
 
3.3%
Other values (14) 216
 
3.2%
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: 1
Text

Distinct1095
Distinct (%)98.9%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:03:54.603545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length8.0352304
Min length2

Characters and Unicode

Total characters8895
Distinct characters625
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1084 ?
Unique (%)97.9%

Sample

1st row조사지점명
2nd rowEXAMIN_SPOT_NM
3rd row평창치안센터(파출소).
4th row구기 빌딩앞(카리스).
5th row우리농산물마트.
ValueCountFrequency (%)
앞 97
 
5.0%
입구 24
 
1.2%
맞은편 17
 
0.9%
아파트 12
 
0.6%
주차장 11
 
0.6%
주택 11
 
0.6%
옆 9
 
0.5%
건물 9
 
0.5%
신한은행 9
 
0.5%
우리은행 9
 
0.5%
Other values (1534) 1750
89.4%
2023-09-17T20:03:55.300243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
851
 
9.6%
동 178
 
2.0%
빌 154
 
1.7%
앞 127
 
1.4%
딩 120
 
1.3%
대 107
 
1.2%
아 98
 
1.1%
리 94
 
1.1%
트 93
 
1.0%
원 89
 
1.0%
Other values (615) 6984
78.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6994
78.6%
Space Separator 851
 
9.6%
Decimal Number 294
 
3.3%
Uppercase Letter 278
 
3.1%
Lowercase Letter 260
 
2.9%
Other Punctuation 75
 
0.8%
Close Punctuation 56
 
0.6%
Open Punctuation 55
 
0.6%
Dash Punctuation 29
 
0.3%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 178
 
2.5%
빌 154
 
2.2%
앞 127
 
1.8%
딩 120
 
1.7%
대 107
 
1.5%
아 98
 
1.4%
리 94
 
1.3%
트 93
 
1.3%
원 89
 
1.3%
점 87
 
1.2%
Other values (546) 5847
83.6%
Uppercase Letter
ValueCountFrequency (%)
S 33
11.9%
T 24
 
8.6%
A 20
 
7.2%
O 19
 
6.8%
G 18
 
6.5%
E 18
 
6.5%
K 18
 
6.5%
N 16
 
5.8%
I 16
 
5.8%
C 15
 
5.4%
Other values (16) 81
29.1%
Lowercase Letter
ValueCountFrequency (%)
e 28
 
10.8%
o 26
 
10.0%
a 25
 
9.6%
r 24
 
9.2%
l 17
 
6.5%
n 15
 
5.8%
m 13
 
5.0%
t 13
 
5.0%
i 12
 
4.6%
c 12
 
4.6%
Other values (12) 75
28.8%
Decimal Number
ValueCountFrequency (%)
1 67
22.8%
2 58
19.7%
0 35
11.9%
5 26
 
8.8%
3 25
 
8.5%
4 20
 
6.8%
8 18
 
6.1%
6 18
 
6.1%
9 14
 
4.8%
7 13
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 61
81.3%
, 8
 
10.7%
& 3
 
4.0%
/ 2
 
2.7%
? 1
 
1.3%
Space Separator
ValueCountFrequency (%)
851
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6991
78.6%
Common 1363
 
15.3%
Latin 538
 
6.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 178
 
2.5%
빌 154
 
2.2%
앞 127
 
1.8%
딩 120
 
1.7%
대 107
 
1.5%
아 98
 
1.4%
리 94
 
1.3%
트 93
 
1.3%
원 89
 
1.3%
점 87
 
1.2%
Other values (544) 5844
83.6%
Latin
ValueCountFrequency (%)
S 33
 
6.1%
e 28
 
5.2%
o 26
 
4.8%
a 25
 
4.6%
r 24
 
4.5%
T 24
 
4.5%
A 20
 
3.7%
O 19
 
3.5%
G 18
 
3.3%
E 18
 
3.3%
Other values (38) 303
56.3%
Common
ValueCountFrequency (%)
851
62.4%
1 67
 
4.9%
. 61
 
4.5%
2 58
 
4.3%
) 56
 
4.1%
( 55
 
4.0%
0 35
 
2.6%
- 29
 
2.1%
5 26
 
1.9%
3 25
 
1.8%
Other values (11) 100
 
7.3%
Han
ValueCountFrequency (%)
內 2
66.7%
前 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6991
78.6%
ASCII 1901
 
21.4%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
851
44.8%
1 67
 
3.5%
. 61
 
3.2%
2 58
 
3.1%
) 56
 
2.9%
( 55
 
2.9%
0 35
 
1.8%
S 33
 
1.7%
- 29
 
1.5%
e 28
 
1.5%
Other values (59) 628
33.0%
Hangul
ValueCountFrequency (%)
동 178
 
2.5%
빌 154
 
2.2%
앞 127
 
1.8%
딩 120
 
1.7%
대 107
 
1.5%
아 98
 
1.4%
리 94
 
1.3%
트 93
 
1.3%
원 89
 
1.3%
점 87
 
1.2%
Other values (544) 5844
83.6%
CJK
ValueCountFrequency (%)
內 2
66.7%
前 1
33.3%

Unnamed: 2
Categorical

Distinct28
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
11020
81 
11220
 
71
11230
 
71
11010
 
66
11110
 
60
Other values (23)
759 

Length

Max length5
Median length5
Mean length4.9972924
Min length3

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
11020 81
 
7.3%
11220 71
 
6.4%
11230 71
 
6.4%
11010 66
 
6.0%
11110 60
 
5.4%
11240 59
 
5.3%
11190 58
 
5.2%
11150 49
 
4.4%
11030 44
 
4.0%
11070 44
 
4.0%
Other values (18) 505
45.6%

Length

2023-09-17T20:03:55.547072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11020 81
 
7.3%
11220 71
 
6.4%
11230 71
 
6.4%
11010 66
 
6.0%
11110 60
 
5.4%
11240 59
 
5.3%
11190 58
 
5.2%
11150 49
 
4.4%
11030 44
 
4.0%
11070 44
 
4.0%
Other values (18) 505
45.6%

Unnamed: 3
Text

Distinct347
Distinct (%)31.3%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:03:56.068697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9963866
Min length3

Characters and Unicode

Total characters7745
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

Unique90 ?
Unique (%)8.1%

Sample

1st row동코드
2nd rowDONG_CD
3rd row1101056
4th row1101056
5th row1101055
ValueCountFrequency (%)
1102055 32
 
2.9%
1101061 25
 
2.3%
1119054 13
 
1.2%
1111079 12
 
1.1%
1106081 12
 
1.1%
1115072 12
 
1.1%
1122053 12
 
1.1%
1119074 10
 
0.9%
1122055 10
 
0.9%
1102052 10
 
0.9%
Other values (337) 959
86.6%
2023-09-17T20:03:56.941904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2912
37.6%
0 1648
21.3%
5 639
 
8.3%
2 615
 
7.9%
6 526
 
6.8%
7 459
 
5.9%
4 281
 
3.6%
3 273
 
3.5%
8 206
 
2.7%
9 176
 
2.3%
Other values (9) 10
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7735
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 2912
37.6%
0 1648
21.3%
5 639
 
8.3%
2 615
 
8.0%
6 526
 
6.8%
7 459
 
5.9%
4 281
 
3.6%
3 273
 
3.5%
8 206
 
2.7%
9 176
 
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 7736
99.9%
Latin 6
 
0.1%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2912
37.6%
0 1648
21.3%
5 639
 
8.3%
2 615
 
7.9%
6 526
 
6.8%
7 459
 
5.9%
4 281
 
3.6%
3 273
 
3.5%
8 206
 
2.7%
9 176
 
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 7742
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2912
37.6%
0 1648
21.3%
5 639
 
8.3%
2 615
 
7.9%
6 526
 
6.8%
7 459
 
5.9%
4 281
 
3.6%
3 273
 
3.5%
8 206
 
2.7%
9 176
 
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

Distinct623
Distinct (%)56.3%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:03:57.645782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7271906
Min length1

Characters and Unicode

Total characters3019
Distinct characters29
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

Unique377 ?
Unique (%)34.1%

Sample

1st row주번지
2nd rowBUNJI
3rd row232
4th row110
5th row94
ValueCountFrequency (%)
1 12
 
1.1%
50 11
 
1.0%
18 10
 
0.9%
19 9
 
0.8%
35 8
 
0.7%
43 8
 
0.7%
7 7
 
0.6%
5 7
 
0.6%
17 7
 
0.6%
2 7
 
0.6%
Other values (613) 1021
92.2%
2023-09-17T20:03:58.659950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 540
17.9%
2 365
12.1%
3 331
11.0%
5 288
9.5%
4 282
9.3%
6 270
8.9%
9 242
8.0%
0 240
7.9%
7 227
7.5%
8 204
 
6.8%
Other values (19) 30
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2989
99.0%
Other Letter 16
 
0.5%
Dash Punctuation 8
 
0.3%
Uppercase Letter 5
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3
18.8%
없 2
12.5%
음 2
12.5%
번 1
 
6.2%
지 1
 
6.2%
주 1
 
6.2%
아 1
 
6.2%
트 1
 
6.2%
파 1
 
6.2%
롱 1
 
6.2%
Other values (2) 2
12.5%
Decimal Number
ValueCountFrequency (%)
1 540
18.1%
2 365
12.2%
3 331
11.1%
5 288
9.6%
4 282
9.4%
6 270
9.0%
9 242
8.1%
0 240
8.0%
7 227
7.6%
8 204
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
N 1
20.0%
I 1
20.0%
J 1
20.0%
U 1
20.0%
B 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2998
99.3%
Hangul 16
 
0.5%
Latin 5
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 540
18.0%
2 365
12.2%
3 331
11.0%
5 288
9.6%
4 282
9.4%
6 270
9.0%
9 242
8.1%
0 240
8.0%
7 227
7.6%
8 204
 
6.8%
Other values (2) 9
 
0.3%
Hangul
ValueCountFrequency (%)
산 3
18.8%
없 2
12.5%
음 2
12.5%
번 1
 
6.2%
지 1
 
6.2%
주 1
 
6.2%
아 1
 
6.2%
트 1
 
6.2%
파 1
 
6.2%
롱 1
 
6.2%
Other values (2) 2
12.5%
Latin
ValueCountFrequency (%)
N 1
20.0%
I 1
20.0%
J 1
20.0%
U 1
20.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3003
99.5%
Hangul 16
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 540
18.0%
2 365
12.2%
3 331
11.0%
5 288
9.6%
4 282
9.4%
6 270
9.0%
9 242
8.1%
0 240
8.0%
7 227
7.6%
8 204
 
6.8%
Other values (7) 14
 
0.5%
Hangul
ValueCountFrequency (%)
산 3
18.8%
없 2
12.5%
음 2
12.5%
번 1
 
6.2%
지 1
 
6.2%
주 1
 
6.2%
아 1
 
6.2%
트 1
 
6.2%
파 1
 
6.2%
롱 1
 
6.2%
Other values (2) 2
12.5%

Unnamed: 5
Text

MISSING 

Distinct132
Distinct (%)15.1%
Missing235
Missing (%)21.2%
Memory size8.8 KiB
2023-09-17T20:03:59.144225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.5315006
Min length1

Characters and Unicode

Total characters1337
Distinct characters16
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

Unique55 ?
Unique (%)6.3%

Sample

1st row부번지
2nd rowBUBUN
3rd row12
4th row2
5th row5
ValueCountFrequency (%)
1 142
 
16.3%
2 56
 
6.4%
3 54
 
6.2%
4 47
 
5.4%
5 46
 
5.3%
6 33
 
3.8%
7 32
 
3.7%
8 27
 
3.1%
10 23
 
2.6%
9 21
 
2.4%
Other values (122) 392
44.9%
2023-09-17T20:03:59.888754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 345
25.8%
2 187
14.0%
3 160
12.0%
5 127
 
9.5%
4 121
 
9.1%
6 98
 
7.3%
7 85
 
6.4%
9 77
 
5.8%
0 66
 
4.9%
8 63
 
4.7%
Other values (6) 8
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1329
99.4%
Uppercase Letter 5
 
0.4%
Other Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 345
26.0%
2 187
14.1%
3 160
12.0%
5 127
 
9.6%
4 121
 
9.1%
6 98
 
7.4%
7 85
 
6.4%
9 77
 
5.8%
0 66
 
5.0%
8 63
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
U 2
40.0%
N 1
20.0%
Other Letter
ValueCountFrequency (%)
부 1
33.3%
번 1
33.3%
지 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1329
99.4%
Latin 5
 
0.4%
Hangul 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 345
26.0%
2 187
14.1%
3 160
12.0%
5 127
 
9.6%
4 121
 
9.1%
6 98
 
7.4%
7 85
 
6.4%
9 77
 
5.8%
0 66
 
5.0%
8 63
 
4.7%
Latin
ValueCountFrequency (%)
B 2
40.0%
U 2
40.0%
N 1
20.0%
Hangul
ValueCountFrequency (%)
부 1
33.3%
번 1
33.3%
지 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1334
99.8%
Hangul 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 345
25.9%
2 187
14.0%
3 160
12.0%
5 127
 
9.5%
4 121
 
9.1%
6 98
 
7.3%
7 85
 
6.4%
9 77
 
5.8%
0 66
 
4.9%
8 63
 
4.7%
Other values (3) 5
 
0.4%
Hangul
ValueCountFrequency (%)
부 1
33.3%
번 1
33.3%
지 1
33.3%

Unnamed: 6
Text

MISSING 

Distinct1010
Distinct (%)99.1%
Missing89
Missing (%)8.0%
Memory size8.8 KiB
2023-09-17T20:04:00.474726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.407262
Min length2

Characters and Unicode

Total characters9586
Distinct characters274
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1006 ?
Unique (%)98.7%

Sample

1st row도로명
2nd rowROAD_NM
3rd row평창문화로 46
4th row진흥로 436
5th row세검정로 230
ValueCountFrequency (%)
서울 169
 
6.9%
노원구 41
 
1.7%
성북구 36
 
1.5%
동대문구 35
 
1.4%
중랑구 31
 
1.3%
광진구 28
 
1.1%
성동구 26
 
1.1%
강북구 22
 
0.9%
도봉구 18
 
0.7%
서울시 17
 
0.7%
Other values (1069) 2037
82.8%
2023-09-17T20:04:01.273451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1451
 
15.1%
로 973
 
10.2%
1 597
 
6.2%
2 459
 
4.8%
3 330
 
3.4%
4 285
 
3.0%
구 269
 
2.8%
길 260
 
2.7%
6 260
 
2.7%
7 238
 
2.5%
Other values (264) 4464
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4986
52.0%
Decimal Number 3041
31.7%
Space Separator 1451
 
15.1%
Dash Punctuation 89
 
0.9%
Uppercase Letter 6
 
0.1%
Connector Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 973
 
19.5%
구 269
 
5.4%
길 260
 
5.2%
서 226
 
4.5%
울 190
 
3.8%
동 180
 
3.6%
대 172
 
3.4%
성 85
 
1.7%
중 78
 
1.6%
북 70
 
1.4%
Other values (239) 2483
49.8%
Decimal Number
ValueCountFrequency (%)
1 597
19.6%
2 459
15.1%
3 330
10.9%
4 285
9.4%
6 260
8.5%
7 238
 
7.8%
5 237
 
7.8%
8 212
 
7.0%
9 212
 
7.0%
0 211
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
A 1
16.7%
M 1
16.7%
N 1
16.7%
D 1
16.7%
O 1
16.7%
R 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 1
33.3%
# 1
33.3%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
1451
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4986
52.0%
Common 4594
47.9%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 973
 
19.5%
구 269
 
5.4%
길 260
 
5.2%
서 226
 
4.5%
울 190
 
3.8%
동 180
 
3.6%
대 172
 
3.4%
성 85
 
1.7%
중 78
 
1.6%
북 70
 
1.4%
Other values (239) 2483
49.8%
Common
ValueCountFrequency (%)
1451
31.6%
1 597
13.0%
2 459
 
10.0%
3 330
 
7.2%
4 285
 
6.2%
6 260
 
5.7%
7 238
 
5.2%
5 237
 
5.2%
8 212
 
4.6%
9 212
 
4.6%
Other values (9) 313
 
6.8%
Latin
ValueCountFrequency (%)
A 1
16.7%
M 1
16.7%
N 1
16.7%
D 1
16.7%
O 1
16.7%
R 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4985
52.0%
ASCII 4600
48.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1451
31.5%
1 597
13.0%
2 459
 
10.0%
3 330
 
7.2%
4 285
 
6.2%
6 260
 
5.7%
7 238
 
5.2%
5 237
 
5.2%
8 212
 
4.6%
9 212
 
4.6%
Other values (15) 319
 
6.9%
Hangul
ValueCountFrequency (%)
로 973
 
19.5%
구 269
 
5.4%
길 260
 
5.2%
서 226
 
4.5%
울 190
 
3.8%
동 180
 
3.6%
대 172
 
3.5%
성 85
 
1.7%
중 78
 
1.6%
북 70
 
1.4%
Other values (238) 2482
49.8%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

Unnamed: 7
Text

Distinct124
Distinct (%)11.2%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:04:01.772450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.9476061
Min length1

Characters and Unicode

Total characters2156
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

Unique47 ?
Unique (%)4.2%

Sample

1st row보도너비
2nd rowFTPTH_BT
3rd row3
4th row3.7
5th row3
ValueCountFrequency (%)
4 129
 
11.7%
3 124
 
11.2%
5 105
 
9.5%
2 83
 
7.5%
6 61
 
5.5%
2.5 46
 
4.2%
3.5 41
 
3.7%
8 40
 
3.6%
4.5 30
 
2.7%
7 30
 
2.7%
Other values (114) 418
37.8%
2023-09-17T20:04:02.470065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 457
21.2%
5 357
16.6%
2 275
12.8%
3 258
12.0%
4 225
10.4%
1 169
 
7.8%
6 133
 
6.2%
8 116
 
5.4%
7 89
 
4.1%
9 39
 
1.8%
Other values (11) 38
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1687
78.2%
Other Punctuation 457
 
21.2%
Uppercase Letter 7
 
0.3%
Other Letter 4
 
0.2%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 357
21.2%
2 275
16.3%
3 258
15.3%
4 225
13.3%
1 169
10.0%
6 133
 
7.9%
8 116
 
6.9%
7 89
 
5.3%
9 39
 
2.3%
0 26
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
T 3
42.9%
F 1
 
14.3%
P 1
 
14.3%
H 1
 
14.3%
B 1
 
14.3%
Other Letter
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
너 1
25.0%
비 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 457
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2145
99.5%
Latin 7
 
0.3%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 457
21.3%
5 357
16.6%
2 275
12.8%
3 258
12.0%
4 225
10.5%
1 169
 
7.9%
6 133
 
6.2%
8 116
 
5.4%
7 89
 
4.1%
9 39
 
1.8%
Other values (2) 27
 
1.3%
Latin
ValueCountFrequency (%)
T 3
42.9%
F 1
 
14.3%
P 1
 
14.3%
H 1
 
14.3%
B 1
 
14.3%
Hangul
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
너 1
25.0%
비 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2152
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 457
21.2%
5 357
16.6%
2 275
12.8%
3 258
12.0%
4 225
10.5%
1 169
 
7.9%
6 133
 
6.2%
8 116
 
5.4%
7 89
 
4.1%
9 39
 
1.8%
Other values (7) 34
 
1.6%
Hangul
ValueCountFrequency (%)
보 1
25.0%
도 1
25.0%
너 1
25.0%
비 1
25.0%

Unnamed: 8
Categorical

Distinct17
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
4
217 
1
211 
6
200 
2
130 
8
99 
Other values (12)
251 

Length

Max length6
Median length1
Mean length1.0460289
Min length1

Unique

Unique5 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row차선수
3rd rowTFCLNE
4th row5
5th row6

Common Values

ValueCountFrequency (%)
4 217
19.6%
1 211
19.0%
6 200
18.1%
2 130
11.7%
8 99
8.9%
5 84
 
7.6%
7 59
 
5.3%
3 39
 
3.5%
10 28
 
2.5%
9 25
 
2.3%
Other values (7) 16
 
1.4%

Length

2023-09-17T20:04:02.719350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 217
19.6%
1 211
19.0%
6 200
18.1%
2 130
11.7%
8 99
8.9%
5 84
 
7.6%
7 59
 
5.3%
3 39
 
3.5%
10 28
 
2.5%
9 25
 
2.3%
Other values (7) 16
 
1.4%

Unnamed: 9
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2
916 
1
189 
<NA>
 
1
버스차로유무
 
1
BUS_CARTRK_ENNC_SE
 
1

Length

Max length18
Median length1
Mean length1.0225632
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row버스차로유무
3rd rowBUS_CARTRK_ENNC_SE
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 916
82.7%
1 189
 
17.1%
<NA> 1
 
0.1%
버스차로유무 1
 
0.1%
BUS_CARTRK_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:02.927776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:03.115980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 916
82.7%
1 189
 
17.1%
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 size8.8 KiB
1
876 
2
229 
<NA>
 
1
중앙선여부
 
1
CTLN_AT_SE
 
1

Length

Max length10
Median length1
Mean length1.0144404
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row중앙선여부
3rd rowCTLN_AT_SE
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 876
79.1%
2 229
 
20.7%
<NA> 1
 
0.1%
중앙선여부 1
 
0.1%
CTLN_AT_SE 1
 
0.1%

Length

2023-09-17T20:04:03.301996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:03.461319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 876
79.1%
2 229
 
20.7%
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 size8.8 KiB
1
1034 
2
 
70
<NA>
 
2
장애물유무
 
1
OBSTC_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0198556
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row장애물유무
3rd rowOBSTC_ENNC_SE
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1034
93.3%
2 70
 
6.3%
<NA> 2
 
0.2%
장애물유무 1
 
0.1%
OBSTC_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:03.716079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:03.972143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1034
93.3%
2 70
 
6.3%
na 2
 
0.2%
장애물유무 1
 
0.1%
obstc_ennc_se 1
 
0.1%

Unnamed: 12
Categorical

Distinct19
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
10
424 
1
151 
17
134 
12
104 
<NA>
73 
Other values (14)
222 

Length

Max length12
Median length2
Mean length1.9422383
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row장애물종류
3rd rowOBSTC_KND_CL
4th row11
5th row10

Common Values

ValueCountFrequency (%)
10 424
38.3%
1 151
 
13.6%
17 134
 
12.1%
12 104
 
9.4%
<NA> 73
 
6.6%
16 68
 
6.1%
18 54
 
4.9%
11 24
 
2.2%
2 22
 
2.0%
8 16
 
1.4%
Other values (9) 38
 
3.4%

Length

2023-09-17T20:04:04.230319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 424
38.3%
1 151
 
13.6%
17 134
 
12.1%
12 104
 
9.4%
na 73
 
6.6%
16 68
 
6.1%
18 54
 
4.9%
11 24
 
2.2%
2 22
 
2.0%
8 16
 
1.4%
Other values (9) 38
 
3.4%

Unnamed: 13
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
1
841 
2
188 
3
 
76
<NA>
 
1
보행도로구분
 
1

Length

Max length12
Median length1
Mean length1.017148
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row보행도로구분
3rd rowWALK_ROAD_SE
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 841
75.9%
2 188
 
17.0%
3 76
 
6.9%
<NA> 1
 
0.1%
보행도로구분 1
 
0.1%
WALK_ROAD_SE 1
 
0.1%

Length

2023-09-17T20:04:04.448482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:04.652863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 841
75.9%
2 188
 
17.0%
3 76
 
6.9%
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 size8.8 KiB
2
572 
1
533 
<NA>
 
1
점자블록유무
 
1
BRLL_BLCK_ENNC_SE
 
1

Length

Max length17
Median length1
Mean length1.0216606
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row점자블록유무
3rd rowBRLL_BLCK_ENNC_SE
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 572
51.6%
1 533
48.1%
<NA> 1
 
0.1%
점자블록유무 1
 
0.1%
BRLL_BLCK_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:04.848286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:05.017394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 572
51.6%
1 533
48.1%
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 size8.8 KiB
2
826 
1
279 
<NA>
 
1
경사로유무
 
1
SLPW__ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.017148
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row경사로유무
3rd rowSLPW__ENNC_SE
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 826
74.5%
1 279
 
25.2%
<NA> 1
 
0.1%
경사로유무 1
 
0.1%
SLPW__ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:05.199984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:05.353566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 826
74.5%
1 279
 
25.2%
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 size8.8 KiB
2
827 
1
278 
<NA>
 
1
펜스유무
 
1
FENC_ENNC_SE
 
1

Length

Max length12
Median length1
Mean length1.015343
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row펜스유무
3rd rowFENC_ENNC_SE
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 827
74.6%
1 278
 
25.1%
<NA> 1
 
0.1%
펜스유무 1
 
0.1%
FENC_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:05.548956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:05.722180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 827
74.6%
1 278
 
25.1%
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 size8.8 KiB
1
622 
2
483 
<NA>
 
1
버스정류장유무
 
1
BUS_STOPG_IPLA_ENNC_SE
 
1

Length

Max length22
Median length1
Mean length1.0270758
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row버스정류장유무
3rd rowBUS_STOPG_IPLA_ENNC_SE
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 622
56.1%
2 483
43.6%
<NA> 1
 
0.1%
버스정류장유무 1
 
0.1%
BUS_STOPG_IPLA_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:05.887633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:06.056746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 622
56.1%
2 483
43.6%
na 1
 
0.1%
버스정류장유무 1
 
0.1%
bus_stopg_ipla_ennc_se 1
 
0.1%

Unnamed: 18
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:06.276106image/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%
2023-09-17T20:04:06.680347image/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 size8.8 KiB
2
897 
1
208 
<NA>
 
1
지하철유무
 
1
SUBWAY_ENNC_SE
 
1

Length

Max length14
Median length1
Mean length1.0180505
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row지하철유무
3rd rowSUBWAY_ENNC_SE
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 897
81.0%
1 208
 
18.8%
<NA> 1
 
0.1%
지하철유무 1
 
0.1%
SUBWAY_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:06.870985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:07.048234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 897
81.0%
1 208
 
18.8%
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 size8.8 KiB
1
800 
2
305 
<NA>
 
1
횡단보도유무
 
1
CRSLK_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0180505
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row횡단보도유무
3rd rowCRSLK_ENNC_SE
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 800
72.2%
2 305
 
27.5%
<NA> 1
 
0.1%
횡단보도유무 1
 
0.1%
CRSLK_ENNC_SE 1
 
0.1%

Length

2023-09-17T20:04:07.219462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:07.382244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 800
72.2%
2 305
 
27.5%
na 1
 
0.1%
횡단보도유무 1
 
0.1%
crslk_ennc_se 1
 
0.1%

Unnamed: 21
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:07.587703image/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%
2023-09-17T20:04:07.991979image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:08.197824image/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%
2023-09-17T20:04:08.582239image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:08.832833image/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%
2023-09-17T20:04:09.248498image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:09.800850image/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%
2023-09-17T20:04:10.253847image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:10.514596image/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%
2023-09-17T20:04:11.017714image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:11.247815image/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%
2023-09-17T20:04:11.682450image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:11.934397image/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%
2023-09-17T20:04:12.414255image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:12.681879image/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%
2023-09-17T20:04:13.144358image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:13.379209image/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%
2023-09-17T20:04:13.833901image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:14.067557image/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%
2023-09-17T20:04:14.501388image/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%
Missing1106
Missing (%)99.8%
Memory size8.8 KiB
2023-09-17T20:04:14.722524image/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%
2023-09-17T20:04:15.182144image/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
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.1%
Memory size8.8 KiB

Unnamed: 33
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.1%
Memory size8.8 KiB

Unnamed: 34
Text

Distinct937
Distinct (%)84.6%
Missing1
Missing (%)0.1%
Memory size8.8 KiB
2023-09-17T20:04:15.582934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.988257
Min length5

Characters and Unicode

Total characters14378
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

Unique843 ?
Unique (%)76.2%

Sample

1st row집계구코드
2nd rowSM_GU_CD
3rd row1101056030004
4th row1101056040001
5th row1101055020005
ValueCountFrequency (%)
1102055060001 28
 
2.5%
1101061040001 11
 
1.0%
1102052020001 8
 
0.7%
1102054070001 6
 
0.5%
1101061030002 6
 
0.5%
1101061020001 6
 
0.5%
1118051030001 4
 
0.4%
1115064010007 4
 
0.4%
1101063040001 4
 
0.4%
1112073010007 3
 
0.3%
Other values (927) 1027
92.8%
2023-09-17T20:04:16.206108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5848
40.7%
1 3777
26.3%
2 1167
 
8.1%
5 789
 
5.5%
6 661
 
4.6%
3 580
 
4.0%
7 543
 
3.8%
4 506
 
3.5%
8 280
 
1.9%
9 214
 
1.5%
Other values (12) 13
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14365
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 5848
40.7%
1 3777
26.3%
2 1167
 
8.1%
5 789
 
5.5%
6 661
 
4.6%
3 580
 
4.0%
7 543
 
3.8%
4 506
 
3.5%
8 280
 
1.9%
9 214
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
M 1
16.7%
C 1
16.7%
U 1
16.7%
G 1
16.7%
S 1
16.7%
Other Letter
ValueCountFrequency (%)
코 1
20.0%
구 1
20.0%
계 1
20.0%
집 1
20.0%
드 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14367
99.9%
Latin 6
 
< 0.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5848
40.7%
1 3777
26.3%
2 1167
 
8.1%
5 789
 
5.5%
6 661
 
4.6%
3 580
 
4.0%
7 543
 
3.8%
4 506
 
3.5%
8 280
 
1.9%
9 214
 
1.5%
Latin
ValueCountFrequency (%)
D 1
16.7%
M 1
16.7%
C 1
16.7%
U 1
16.7%
G 1
16.7%
S 1
16.7%
Hangul
ValueCountFrequency (%)
코 1
20.0%
구 1
20.0%
계 1
20.0%
집 1
20.0%
드 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14373
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5848
40.7%
1 3777
26.3%
2 1167
 
8.1%
5 789
 
5.5%
6 661
 
4.6%
3 580
 
4.0%
7 543
 
3.8%
4 506
 
3.5%
8 280
 
1.9%
9 214
 
1.5%
Other values (7) 8
 
0.1%
Hangul
ValueCountFrequency (%)
코 1
20.0%
구 1
20.0%
계 1
20.0%
집 1
20.0%
드 1
20.0%

Unnamed: 35
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2014
1105 
<NA>
 
1
년도
 
1
YEAR
 
1

Length

Max length4
Median length4
Mean length3.9981949
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row년도
3rd rowYEAR
4th row2014
5th row2014

Common Values

ValueCountFrequency (%)
2014 1105
99.7%
<NA> 1
 
0.1%
년도 1
 
0.1%
YEAR 1
 
0.1%

Length

2023-09-17T20:04:16.444677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:16.615617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2014 1105
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 size8.8 KiB
본조사
1105 
<NA>
 
1
조사구분
 
1
EXAMIN_CLS
 
1

Length

Max length10
Median length3
Mean length3.0081227
Min length3

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
본조사 1105
99.7%
<NA> 1
 
0.1%
조사구분 1
 
0.1%
EXAMIN_CLS 1
 
0.1%

Length

2023-09-17T20:04:16.791397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-17T20:04:16.952313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본조사 1105
99.7%
na 1
 
0.1%
조사구분 1
 
0.1%
examin_cls 1
 
0.1%

Sample

유동인구_조사지점정보_2014Unnamed: 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>NaNNaN<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
301-001평창치안센터(파출소).110101101056232<NA>평창문화로 46352111112221<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>197049.74567456193.2247211010560300042014본조사
401-002구기 빌딩앞(카리스).11010110105611012진흥로 4363.762111012122<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>196222.46838456497.427411010560400012014본조사
501-004우리농산물마트.110101101055942세검정로 230372111031221<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>196315.80243455621.3826211010550200052014본조사
601-007국민대학교 삼림과학대학 실습장110101101056815없음342111011121<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>197662.28452456614.7683911010560200082014본조사
701-011다이소 종묘점110201102059290<NA>종로 3395.52222<NA>12221<NA>11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>200784.37163452206.7839511020590800012014본조사
801-012뉴경신 숙녀화.11020110206943665청계천로 3194.54222<NA>12221<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>201191.14551452230.113911020690200012014본조사
901-013대광약국.1101011010632312종로 2446.58212<NA>12211<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>200425.50936452379.9743311010630400012014본조사
유동인구_조사지점정보_2014Unnamed: 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
109825-088SKT핸드폰 대리점1125011250733342올림픽로 693742111231222<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211061.86862449308.9287911250730200212014본조사
109925-092르카프 할인상설매장11250112507492<NA>명일로 26042211111211<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>213020.33181449091.739111250740200122014본조사
110025-1904신동아인테리어11250112505444<NA>고덕로 2403.712111212112<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>213444.55455450578.3714111250540101012014본조사
110125-1918국민은행강동영업지원본부1125011250744573천호대로 1129891111031121<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212254.15237448350.5329511250740400082014본조사
110225-2026춘천족발11250112507341756구천면로25길 33.642111011212<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211173.8743449027.098411250730200052014본조사
110325-238시장 농협 양국 판매점1125011250743636양재대로116길 49512211622222<NA>22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212673.15049448730.0182611250740520012014본조사
110425-408한국전기공사와 명성프라자 사이112501125054461고덕로 256105211811222<NA>12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>213634.65495450570.3929511250540100082014본조사
110525-430신동아생활용품DC마트1125011250724922상암로11길 245.512211612222<NA>22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211375.75228450168.3329711250720200012014본조사
110625-815황가 손칼국수 음식점1125011250661923천호대로 10968.29111811122<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211778.66913448392.4805511250660205012014본조사
110725-816낙지마을11250112506638315성안로 119-54.322111812222<NA>21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>211766.43518448320.3448711250660200052014본조사