Overview

Dataset statistics

Number of variables37
Number of observations9871
Missing cells110440
Missing cells (%)30.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory296.0 B

Variable types

Text20
Categorical17

Dataset

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

Alerts

Unnamed: 9 is highly imbalanced (56.8%)Imbalance
Unnamed: 10 is highly imbalanced (56.8%)Imbalance
Unnamed: 11 is highly imbalanced (81.3%)Imbalance
Unnamed: 13 is highly imbalanced (52.9%)Imbalance
Unnamed: 14 is highly imbalanced (64.2%)Imbalance
Unnamed: 15 is highly imbalanced (64.7%)Imbalance
Unnamed: 16 is highly imbalanced (73.1%)Imbalance
Unnamed: 17 is highly imbalanced (64.9%)Imbalance
Unnamed: 19 is highly imbalanced (64.9%)Imbalance
Unnamed: 20 is highly imbalanced (56.9%)Imbalance
Unnamed: 35 is highly imbalanced (99.8%)Imbalance
Unnamed: 36 is highly imbalanced (98.8%)Imbalance
Unnamed: 6 has 1694 (17.2%) missing valuesMissing
Unnamed: 18 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 21 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 22 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 23 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 24 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 25 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 26 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 27 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 28 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 30 has 9869 (> 99.9%) missing valuesMissing
Unnamed: 31 has 9869 (> 99.9%) missing valuesMissing

Reproduction

Analysis started2023-12-11 06:16:01.207222
Analysis finished2023-12-11 06:16:03.893932
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유동인구_조사지점정보_2012
Text

Distinct9870
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size77.2 KiB
2023-12-11T15:16:04.246408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.38308
Min length6

Characters and Unicode

Total characters63001
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

Unique9870 ?
Unique (%)100.0%

Sample

1st row조사지점코드
2nd rowEXAMIN_SPOT_CD
3rd row01-001
4th row01-002
5th row01-003
ValueCountFrequency (%)
01-005 1
 
< 0.1%
19-079 1
 
< 0.1%
19-067 1
 
< 0.1%
19-095 1
 
< 0.1%
19-068 1
 
< 0.1%
19-069 1
 
< 0.1%
19-076 1
 
< 0.1%
19-077 1
 
< 0.1%
19-078 1
 
< 0.1%
19-080 1
 
< 0.1%
Other values (9860) 9860
99.9%
2023-12-11T15:16:04.885505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11003
17.5%
- 9868
15.7%
1 9858
15.6%
2 9588
15.2%
3 5519
8.8%
4 3930
 
6.2%
5 2995
 
4.8%
8 2703
 
4.3%
6 2606
 
4.1%
9 2462
 
3.9%
Other values (20) 2469
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53113
84.3%
Dash Punctuation 9868
 
15.7%
Uppercase Letter 12
 
< 0.1%
Other Letter 6
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 1
8.3%
D 1
8.3%
C 1
8.3%
O 1
8.3%
P 1
8.3%
S 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 11003
20.7%
1 9858
18.6%
2 9588
18.1%
3 5519
10.4%
4 3930
 
7.4%
5 2995
 
5.6%
8 2703
 
5.1%
6 2606
 
4.9%
9 2462
 
4.6%
7 2449
 
4.6%
Other Letter
ValueCountFrequency (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
조 1
16.7%
사 1
16.7%
드 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 9868
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62983
> 99.9%
Latin 12
 
< 0.1%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11003
17.5%
- 9868
15.7%
1 9858
15.7%
2 9588
15.2%
3 5519
8.8%
4 3930
 
6.2%
5 2995
 
4.8%
8 2703
 
4.3%
6 2606
 
4.1%
9 2462
 
3.9%
Other values (2) 2451
 
3.9%
Latin
ValueCountFrequency (%)
T 1
8.3%
D 1
8.3%
C 1
8.3%
O 1
8.3%
P 1
8.3%
S 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 (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
조 1
16.7%
사 1
16.7%
드 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62995
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11003
17.5%
- 9868
15.7%
1 9858
15.6%
2 9588
15.2%
3 5519
8.8%
4 3930
 
6.2%
5 2995
 
4.8%
8 2703
 
4.3%
6 2606
 
4.1%
9 2462
 
3.9%
Other values (14) 2463
 
3.9%
Hangul
ValueCountFrequency (%)
코 1
16.7%
점 1
16.7%
지 1
16.7%
조 1
16.7%
사 1
16.7%
드 1
16.7%

Unnamed: 1
Text

Distinct9480
Distinct (%)96.0%
Missing1
Missing (%)< 0.1%
Memory size77.2 KiB
2023-12-11T15:16:05.296890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length29
Mean length8.1514691
Min length1

Characters and Unicode

Total characters80455
Distinct characters980
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9249 ?
Unique (%)93.7%

Sample

1st row조사지점명
2nd rowEXAMIN_SPOT_NM
3rd row평창치안센터(파출소).
4th row구기 빌딩앞(카리스).
5th row신흥모피명품전문크리닝.
ValueCountFrequency (%)
앞 404
 
2.3%
주택 287
 
1.6%
입구 140
 
0.8%
맞은편 134
 
0.8%
아파트 117
 
0.7%
옆 116
 
0.7%
주차장 106
 
0.6%
건너편 98
 
0.6%
빌라 96
 
0.5%
일반주택 67
 
0.4%
Other values (11018) 16021
91.1%
2023-12-11T15:16:05.830932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7716
 
9.6%
동 1913
 
2.4%
빌 1430
 
1.8%
1 1159
 
1.4%
주 1117
 
1.4%
아 964
 
1.2%
트 940
 
1.2%
대 884
 
1.1%
딩 836
 
1.0%
지 835
 
1.0%
Other values (970) 62661
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61550
76.5%
Space Separator 7717
 
9.6%
Decimal Number 5170
 
6.4%
Uppercase Letter 2405
 
3.0%
Lowercase Letter 1618
 
2.0%
Dash Punctuation 587
 
0.7%
Open Punctuation 536
 
0.7%
Close Punctuation 532
 
0.7%
Other Punctuation 303
 
0.4%
Modifier Symbol 15
 
< 0.1%
Other values (6) 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1913
 
3.1%
빌 1430
 
2.3%
주 1117
 
1.8%
아 964
 
1.6%
트 940
 
1.5%
대 884
 
1.4%
딩 836
 
1.4%
지 835
 
1.4%
이 794
 
1.3%
원 771
 
1.3%
Other values (881) 51066
83.0%
Uppercase Letter
ValueCountFrequency (%)
S 256
 
10.6%
T 182
 
7.6%
A 172
 
7.2%
K 166
 
6.9%
C 156
 
6.5%
O 136
 
5.7%
E 132
 
5.5%
G 131
 
5.4%
I 112
 
4.7%
B 106
 
4.4%
Other values (16) 856
35.6%
Lowercase Letter
ValueCountFrequency (%)
e 172
 
10.6%
o 146
 
9.0%
a 144
 
8.9%
i 124
 
7.7%
l 108
 
6.7%
t 108
 
6.7%
r 104
 
6.4%
n 95
 
5.9%
s 94
 
5.8%
m 89
 
5.5%
Other values (16) 434
26.8%
Decimal Number
ValueCountFrequency (%)
1 1159
22.4%
2 787
15.2%
3 642
12.4%
0 610
11.8%
5 452
 
8.7%
4 385
 
7.4%
6 344
 
6.7%
7 294
 
5.7%
9 253
 
4.9%
8 244
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 164
54.1%
, 78
25.7%
& 38
 
12.5%
/ 10
 
3.3%
@ 5
 
1.7%
? 3
 
1.0%
" 2
 
0.7%
· 1
 
0.3%
# 1
 
0.3%
: 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
| 2
50.0%
~ 1
25.0%
= 1
25.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅱ 1
25.0%
Ⅵ 1
25.0%
Space Separator
ValueCountFrequency (%)
7716
> 99.9%
　 1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 11
73.3%
^ 4
 
26.7%
Dash Punctuation
ValueCountFrequency (%)
- 587
100.0%
Open Punctuation
ValueCountFrequency (%)
( 536
100.0%
Close Punctuation
ValueCountFrequency (%)
) 532
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Final Punctuation
ValueCountFrequency (%)
” 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61507
76.4%
Common 14875
 
18.5%
Latin 4027
 
5.0%
Han 46
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1913
 
3.1%
빌 1430
 
2.3%
주 1117
 
1.8%
아 964
 
1.6%
트 940
 
1.5%
대 884
 
1.4%
딩 836
 
1.4%
지 835
 
1.4%
이 794
 
1.3%
원 771
 
1.3%
Other values (845) 51023
83.0%
Latin
ValueCountFrequency (%)
S 256
 
6.4%
T 182
 
4.5%
A 172
 
4.3%
e 172
 
4.3%
K 166
 
4.1%
C 156
 
3.9%
o 146
 
3.6%
a 144
 
3.6%
O 136
 
3.4%
E 132
 
3.3%
Other values (45) 2365
58.7%
Han
ValueCountFrequency (%)
內 4
 
8.7%
前 3
 
6.5%
原 2
 
4.3%
家 2
 
4.3%
山 2
 
4.3%
大 2
 
4.3%
宇 1
 
2.2%
逸 1
 
2.2%
明 1
 
2.2%
礎 1
 
2.2%
Other values (27) 27
58.7%
Common
ValueCountFrequency (%)
7716
51.9%
1 1159
 
7.8%
2 787
 
5.3%
3 642
 
4.3%
0 610
 
4.1%
- 587
 
3.9%
( 536
 
3.6%
) 532
 
3.6%
5 452
 
3.0%
4 385
 
2.6%
Other values (23) 1469
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61504
76.4%
ASCII 18892
 
23.5%
CJK 45
 
0.1%
None 5
 
< 0.1%
Punctuation 4
 
< 0.1%
Number Forms 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7716
40.8%
1 1159
 
6.1%
2 787
 
4.2%
3 642
 
3.4%
0 610
 
3.2%
- 587
 
3.1%
( 536
 
2.8%
) 532
 
2.8%
5 452
 
2.4%
4 385
 
2.0%
Other values (71) 5486
29.0%
Hangul
ValueCountFrequency (%)
동 1913
 
3.1%
빌 1430
 
2.3%
주 1117
 
1.8%
아 964
 
1.6%
트 940
 
1.5%
대 884
 
1.4%
딩 836
 
1.4%
지 835
 
1.4%
이 794
 
1.3%
원 771
 
1.3%
Other values (844) 51020
83.0%
CJK
ValueCountFrequency (%)
內 4
 
8.9%
前 3
 
6.7%
原 2
 
4.4%
家 2
 
4.4%
山 2
 
4.4%
大 2
 
4.4%
宇 1
 
2.2%
逸 1
 
2.2%
明 1
 
2.2%
礎 1
 
2.2%
Other values (26) 26
57.8%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 1
 
20.0%
　 1
 
20.0%
Punctuation
ValueCountFrequency (%)
” 2
50.0%
“ 2
50.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅱ 1
25.0%
Ⅵ 1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%

Unnamed: 2
Categorical

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
11230
 
665
11220
 
621
11110
 
607
11190
 
583
11240
 
554
Other values (23)
6841 

Length

Max length5
Median length5
Mean length4.9906798
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
11230 665
 
6.7%
11220 621
 
6.3%
11110 607
 
6.1%
11190 583
 
5.9%
11240 554
 
5.6%
11010 507
 
5.1%
11020 452
 
4.6%
11140 451
 
4.6%
11150 401
 
4.1%
11170 399
 
4.0%
Other values (18) 4631
46.9%

Length

2023-12-11T15:16:05.982655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11230 665
 
6.7%
11220 621
 
6.3%
11110 607
 
6.1%
11190 583
 
5.9%
11240 554
 
5.6%
11010 507
 
5.1%
11020 452
 
4.6%
11140 451
 
4.6%
11150 401
 
4.1%
11170 399
 
4.0%
Other values (18) 4631
46.9%

Unnamed: 3
Text

Distinct413
Distinct (%)4.2%
Missing90
Missing (%)0.9%
Memory size77.2 KiB
2023-12-11T15:16:06.359573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.999591
Min length3

Characters and Unicode

Total characters68463
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

Unique14 ?
Unique (%)0.1%

Sample

1st row동코드
2nd rowDONG_CD
3rd row1101056
4th row1101056
5th row1101055
ValueCountFrequency (%)
1101061 173
 
1.8%
1106081 120
 
1.2%
1119054 118
 
1.2%
1123064 117
 
1.2%
1111079 116
 
1.2%
1115072 99
 
1.0%
1102055 96
 
1.0%
1122055 88
 
0.9%
1102052 88
 
0.9%
1122053 87
 
0.9%
Other values (403) 8679
88.7%
2023-12-11T15:16:06.947162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 26085
38.1%
0 14178
20.7%
5 5554
 
8.1%
2 5465
 
8.0%
6 4729
 
6.9%
7 4098
 
6.0%
4 2479
 
3.6%
3 2431
 
3.6%
8 1751
 
2.6%
9 1683
 
2.5%
Other values (9) 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68453
> 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 26085
38.1%
0 14178
20.7%
5 5554
 
8.1%
2 5465
 
8.0%
6 4729
 
6.9%
7 4098
 
6.0%
4 2479
 
3.6%
3 2431
 
3.6%
8 1751
 
2.6%
9 1683
 
2.5%
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 68454
> 99.9%
Latin 6
 
< 0.1%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 26085
38.1%
0 14178
20.7%
5 5554
 
8.1%
2 5465
 
8.0%
6 4729
 
6.9%
7 4098
 
6.0%
4 2479
 
3.6%
3 2431
 
3.6%
8 1751
 
2.6%
9 1683
 
2.5%
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 68460
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 26085
38.1%
0 14178
20.7%
5 5554
 
8.1%
2 5465
 
8.0%
6 4729
 
6.9%
7 4098
 
6.0%
4 2479
 
3.6%
3 2431
 
3.6%
8 1751
 
2.6%
9 1683
 
2.5%
Other values (6) 7
 
< 0.1%
Hangul
ValueCountFrequency (%)
동 1
33.3%
코 1
33.3%
드 1
33.3%

Unnamed: 4
Text

Distinct1677
Distinct (%)17.0%
Missing17
Missing (%)0.2%
Memory size77.2 KiB
2023-12-11T15:16:07.428101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.7927745
Min length1

Characters and Unicode

Total characters27520
Distinct characters50
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique596 ?
Unique (%)6.0%

Sample

1st row주번지
2nd rowBUNJI
3rd row229
4th row110
5th row127
ValueCountFrequency (%)
1 105
 
1.1%
5 54
 
0.5%
35 49
 
0.5%
50 48
 
0.5%
0 48
 
0.5%
45 46
 
0.5%
10 46
 
0.5%
17 45
 
0.5%
없음 43
 
0.4%
2 43
 
0.4%
Other values (1658) 9323
94.6%
2023-12-11T15:16:08.036084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4674
17.0%
2 3130
11.4%
3 2983
10.8%
4 2658
9.7%
5 2629
9.6%
6 2475
9.0%
7 2281
8.3%
0 2198
8.0%
9 2044
7.4%
8 1987
7.2%
Other values (40) 461
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27059
98.3%
Dash Punctuation 292
 
1.1%
Other Letter 140
 
0.5%
Other Punctuation 16
 
0.1%
Uppercase Letter 6
 
< 0.1%
Space Separator 4
 
< 0.1%
Modifier Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
없 43
30.7%
음 43
30.7%
산 20
14.3%
동 3
 
2.1%
공 3
 
2.1%
주 3
 
2.1%
미 2
 
1.4%
지 2
 
1.4%
기 2
 
1.4%
번 1
 
0.7%
Other values (18) 18
12.9%
Decimal Number
ValueCountFrequency (%)
1 4674
17.3%
2 3130
11.6%
3 2983
11.0%
4 2658
9.8%
5 2629
9.7%
6 2475
9.1%
7 2281
8.4%
0 2198
8.1%
9 2044
7.6%
8 1987
7.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
16.7%
N 1
16.7%
I 1
16.7%
J 1
16.7%
U 1
16.7%
B 1
16.7%
Other Punctuation
ValueCountFrequency (%)
? 15
93.8%
/ 1
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 292
100.0%
Space Separator
ValueCountFrequency (%)
　 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27373
99.5%
Hangul 140
 
0.5%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
없 43
30.7%
음 43
30.7%
산 20
14.3%
동 3
 
2.1%
공 3
 
2.1%
주 3
 
2.1%
미 2
 
1.4%
지 2
 
1.4%
기 2
 
1.4%
번 1
 
0.7%
Other values (18) 18
12.9%
Common
ValueCountFrequency (%)
1 4674
17.1%
2 3130
11.4%
3 2983
10.9%
4 2658
9.7%
5 2629
9.6%
6 2475
9.0%
7 2281
8.3%
0 2198
8.0%
9 2044
7.5%
8 1987
7.3%
Other values (5) 314
 
1.1%
Latin
ValueCountFrequency (%)
K 1
14.3%
o 1
14.3%
N 1
14.3%
I 1
14.3%
J 1
14.3%
U 1
14.3%
B 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27376
99.5%
Hangul 140
 
0.5%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4674
17.1%
2 3130
11.4%
3 2983
10.9%
4 2658
9.7%
5 2629
9.6%
6 2475
9.0%
7 2281
8.3%
0 2198
8.0%
9 2044
7.5%
8 1987
7.3%
Other values (11) 317
 
1.2%
Hangul
ValueCountFrequency (%)
없 43
30.7%
음 43
30.7%
산 20
14.3%
동 3
 
2.1%
공 3
 
2.1%
주 3
 
2.1%
미 2
 
1.4%
지 2
 
1.4%
기 2
 
1.4%
번 1
 
0.7%
Other values (18) 18
12.9%
None
ValueCountFrequency (%)
　 4
100.0%

Unnamed: 5
Text

Distinct369
Distinct (%)3.7%
Missing21
Missing (%)0.2%
Memory size77.2 KiB
2023-12-11T15:16:08.384001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.473198
Min length1

Characters and Unicode

Total characters14511
Distinct characters39
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)1.5%

Sample

1st row부번지
2nd rowBUBUN
3rd row4
4th row12
5th row11
ValueCountFrequency (%)
0 2261
23.0%
1 921
 
9.4%
2 498
 
5.1%
3 405
 
4.1%
4 364
 
3.7%
5 342
 
3.5%
7 267
 
2.7%
6 263
 
2.7%
8 208
 
2.1%
10 202
 
2.1%
Other values (357) 4118
41.8%
2023-12-11T15:16:08.940980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3200
22.1%
0 2890
19.9%
2 1881
13.0%
3 1378
9.5%
4 1159
 
8.0%
5 1026
 
7.1%
6 811
 
5.6%
7 770
 
5.3%
8 707
 
4.9%
9 634
 
4.4%
Other values (29) 55
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14456
99.6%
Other Letter 28
 
0.2%
Other Punctuation 16
 
0.1%
Uppercase Letter 6
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
없 5
17.9%
음 5
17.9%
교 2
 
7.1%
학 2
 
7.1%
지 1
 
3.6%
대 1
 
3.6%
원 1
 
3.6%
공 1
 
3.6%
담 1
 
3.6%
청 1
 
3.6%
Other values (8) 8
28.6%
Decimal Number
ValueCountFrequency (%)
1 3200
22.1%
0 2890
20.0%
2 1881
13.0%
3 1378
9.5%
4 1159
 
8.0%
5 1026
 
7.1%
6 811
 
5.6%
7 770
 
5.3%
8 707
 
4.9%
9 634
 
4.4%
Other Punctuation
ValueCountFrequency (%)
? 11
68.8%
, 3
 
18.8%
/ 1
 
6.2%
. 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
33.3%
U 2
33.3%
G 1
16.7%
N 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Space Separator
ValueCountFrequency (%)
　 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14477
99.8%
Hangul 28
 
0.2%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
없 5
17.9%
음 5
17.9%
교 2
 
7.1%
학 2
 
7.1%
지 1
 
3.6%
대 1
 
3.6%
원 1
 
3.6%
공 1
 
3.6%
담 1
 
3.6%
청 1
 
3.6%
Other values (8) 8
28.6%
Common
ValueCountFrequency (%)
1 3200
22.1%
0 2890
20.0%
2 1881
13.0%
3 1378
9.5%
4 1159
 
8.0%
5 1026
 
7.1%
6 811
 
5.6%
7 770
 
5.3%
8 707
 
4.9%
9 634
 
4.4%
Other values (7) 21
 
0.1%
Latin
ValueCountFrequency (%)
B 2
33.3%
U 2
33.3%
G 1
16.7%
N 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14482
99.8%
Hangul 28
 
0.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3200
22.1%
0 2890
20.0%
2 1881
13.0%
3 1378
9.5%
4 1159
 
8.0%
5 1026
 
7.1%
6 811
 
5.6%
7 770
 
5.3%
8 707
 
4.9%
9 634
 
4.4%
Other values (10) 26
 
0.2%
Hangul
ValueCountFrequency (%)
없 5
17.9%
음 5
17.9%
교 2
 
7.1%
학 2
 
7.1%
지 1
 
3.6%
대 1
 
3.6%
원 1
 
3.6%
공 1
 
3.6%
담 1
 
3.6%
청 1
 
3.6%
Other values (8) 8
28.6%
None
ValueCountFrequency (%)
　 1
100.0%

Unnamed: 6
Text

MISSING 

Distinct4040
Distinct (%)49.4%
Missing1694
Missing (%)17.2%
Memory size77.2 KiB
2023-12-11T15:16:09.359676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length5.1027272
Min length1

Characters and Unicode

Total characters41725
Distinct characters482
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

Unique3060 ?
Unique (%)37.4%

Sample

1st row도로명
2nd rowROAD_NM
3rd row세검정길
4th row세검정길
5th row세검정길
ValueCountFrequency (%)
없음 694
 
6.2%
남부순환로 63
 
0.6%
한천로 59
 
0.5%
강남대로 55
 
0.5%
천호대로 54
 
0.5%
도봉로 48
 
0.4%
구로동길 46
 
0.4%
조사표 44
 
0.4%
경인로 43
 
0.4%
동일로 42
 
0.4%
Other values (3514) 10039
89.7%
2023-12-11T15:16:09.948469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 4518
 
10.8%
로 3691
 
8.8%
3012
 
7.2%
1 1753
 
4.2%
2 1187
 
2.8%
3 947
 
2.3%
동 901
 
2.2%
없 732
 
1.8%
4 722
 
1.7%
음 722
 
1.7%
Other values (472) 23540
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30669
73.5%
Decimal Number 7689
 
18.4%
Space Separator 3012
 
7.2%
Dash Punctuation 209
 
0.5%
Open Punctuation 63
 
0.2%
Close Punctuation 61
 
0.1%
Other Punctuation 12
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Math Symbol 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 4518
 
14.7%
로 3691
 
12.0%
동 901
 
2.9%
없 732
 
2.4%
음 722
 
2.4%
대 589
 
1.9%
산 420
 
1.4%
천 361
 
1.2%
서 334
 
1.1%
사 319
 
1.0%
Other values (445) 18082
59.0%
Decimal Number
ValueCountFrequency (%)
1 1753
22.8%
2 1187
15.4%
3 947
12.3%
4 722
9.4%
5 661
 
8.6%
6 555
 
7.2%
7 538
 
7.0%
8 471
 
6.1%
0 429
 
5.6%
9 426
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
R 1
16.7%
M 1
16.7%
N 1
16.7%
D 1
16.7%
A 1
16.7%
O 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 6
50.0%
, 4
33.3%
# 1
 
8.3%
& 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
3012
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 209
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30667
73.5%
Common 11050
 
26.5%
Latin 6
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 4518
 
14.7%
로 3691
 
12.0%
동 901
 
2.9%
없 732
 
2.4%
음 722
 
2.4%
대 589
 
1.9%
산 420
 
1.4%
천 361
 
1.2%
서 334
 
1.1%
사 319
 
1.0%
Other values (444) 18080
59.0%
Common
ValueCountFrequency (%)
3012
27.3%
1 1753
15.9%
2 1187
 
10.7%
3 947
 
8.6%
4 722
 
6.5%
5 661
 
6.0%
6 555
 
5.0%
7 538
 
4.9%
8 471
 
4.3%
0 429
 
3.9%
Other values (11) 775
 
7.0%
Latin
ValueCountFrequency (%)
R 1
16.7%
M 1
16.7%
N 1
16.7%
D 1
16.7%
A 1
16.7%
O 1
16.7%
Han
ValueCountFrequency (%)
無 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30641
73.4%
ASCII 11056
 
26.5%
Compat Jamo 26
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 4518
 
14.7%
로 3691
 
12.0%
동 901
 
2.9%
없 732
 
2.4%
음 722
 
2.4%
대 589
 
1.9%
산 420
 
1.4%
천 361
 
1.2%
서 334
 
1.1%
사 319
 
1.0%
Other values (439) 18054
58.9%
ASCII
ValueCountFrequency (%)
3012
27.2%
1 1753
15.9%
2 1187
 
10.7%
3 947
 
8.6%
4 722
 
6.5%
5 661
 
6.0%
6 555
 
5.0%
7 538
 
4.9%
8 471
 
4.3%
0 429
 
3.9%
Other values (17) 781
 
7.1%
Compat Jamo
ValueCountFrequency (%)
ㅡ 20
76.9%
ㄴ 2
 
7.7%
ㅍ 2
 
7.7%
ㅁ 1
 
3.8%
ㅈ 1
 
3.8%
CJK
ValueCountFrequency (%)
無 2
100.0%

Unnamed: 7
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
3
2263 
2
1900 
4
1825 
5
1362 
6
854 
Other values (21)
1667 

Length

Max length8
Median length1
Mean length1.0206666
Min length1

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row보도너비
3rd rowFTPTH_BT
4th row3
5th row4

Common Values

ValueCountFrequency (%)
3 2263
22.9%
2 1900
19.2%
4 1825
18.5%
5 1362
13.8%
6 854
 
8.7%
1 532
 
5.4%
7 519
 
5.3%
8 304
 
3.1%
9 117
 
1.2%
10 105
 
1.1%
Other values (16) 90
 
0.9%

Length

2023-12-11T15:16:10.146224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 2263
22.9%
2 1900
19.2%
4 1825
18.5%
5 1362
13.8%
6 854
 
8.7%
1 532
 
5.4%
7 519
 
5.3%
8 304
 
3.1%
9 117
 
1.2%
10 105
 
1.1%
Other values (16) 90
 
0.9%

Unnamed: 8
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
1
4473 
2
1614 
4
1419 
6
946 
8
 
422
Other values (13)
997 

Length

Max length6
Median length1
Mean length1.0183365
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 4473
45.3%
2 1614
 
16.4%
4 1419
 
14.4%
6 946
 
9.6%
8 422
 
4.3%
5 293
 
3.0%
3 239
 
2.4%
7 233
 
2.4%
10 122
 
1.2%
9 58
 
0.6%
Other values (8) 52
 
0.5%

Length

2023-12-11T15:16:10.313423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 4473
45.3%
2 1614
 
16.4%
4 1419
 
14.4%
6 946
 
9.6%
8 422
 
4.3%
5 293
 
3.0%
3 239
 
2.4%
7 233
 
2.4%
10 122
 
1.2%
9 58
 
0.6%
Other values (8) 52
 
0.5%

Unnamed: 9
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
유
5146 
무
4722 
<NA>
 
1
버스차로유무
 
1
BUS_CARTRK_ENNC_SE
 
1

Length

Max length18
Median length1
Mean length1.0025327
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
유 5146
52.1%
무 4722
47.8%
<NA> 1
 
< 0.1%
버스차로유무 1
 
< 0.1%
BUS_CARTRK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:10.473290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:10.579243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 5146
52.1%
무 4722
47.8%
na 1
 
< 0.1%
버스차로유무 1
 
< 0.1%
bus_cartrk_ennc_se 1
 
< 0.1%

Unnamed: 10
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
유
5146 
무
4722 
<NA>
 
1
중앙선여부
 
1
CTLN_AT_SE
 
1

Length

Max length10
Median length1
Mean length1.0016209
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
유 5146
52.1%
무 4722
47.8%
<NA> 1
 
< 0.1%
중앙선여부 1
 
< 0.1%
CTLN_AT_SE 1
 
< 0.1%

Length

2023-12-11T15:16:10.728159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:10.856390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 5146
52.1%
무 4722
47.8%
na 1
 
< 0.1%
중앙선여부 1
 
< 0.1%
ctln_at_se 1
 
< 0.1%

Unnamed: 11
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
유
8998 
무
 
870
<NA>
 
1
장애물유무
 
1
OBSTC_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0019248
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
유 8998
91.2%
무 870
 
8.8%
<NA> 1
 
< 0.1%
장애물유무 1
 
< 0.1%
OBSTC_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:10.970796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:11.071603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 8998
91.2%
무 870
 
8.8%
na 1
 
< 0.1%
장애물유무 1
 
< 0.1%
obstc_ennc_se 1
 
< 0.1%

Unnamed: 12
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
가로수
2559 
기타
2372 
기둥(가로등 등)
1670 
없음
877 
상가 고정 장애물 등
835 
Other values (16)
1558 

Length

Max length12
Median length11
Mean length4.702867
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
가로수 2559
25.9%
기타 2372
24.0%
기둥(가로등 등) 1670
16.9%
없음 877
 
8.9%
상가 고정 장애물 등 835
 
8.5%
불법주정차 714
 
7.2%
신호제어기 141
 
1.4%
가로수 보호대 123
 
1.2%
노점상/가판대 116
 
1.2%
쓰레기통 97
 
1.0%
Other values (11) 367
 
3.7%

Length

2023-12-11T15:16:11.206290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가로수 2682
18.7%
등 2505
17.5%
기타 2372
16.6%
기둥(가로등 1670
11.7%
없음 877
 
6.1%
상가 835
 
5.8%
고정 835
 
5.8%
장애물 835
 
5.8%
불법주정차 714
 
5.0%
신호제어기 141
 
1.0%
Other values (16) 852
 
6.0%

Unnamed: 13
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
보도전용
5495 
보도차도겸용
3888 
자동차겸용
 
485
<NA>
 
1
보행도로구분
 
1

Length

Max length12
Median length4
Mean length4.837909
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
보도전용 5495
55.7%
보도차도겸용 3888
39.4%
자동차겸용 485
 
4.9%
<NA> 1
 
< 0.1%
보행도로구분 1
 
< 0.1%
WALK_ROAD_SE 1
 
< 0.1%

Length

2023-12-11T15:16:11.577270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:11.698528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보도전용 5495
55.7%
보도차도겸용 3888
39.4%
자동차겸용 485
 
4.9%
na 1
 
< 0.1%
보행도로구분 1
 
< 0.1%
walk_road_se 1
 
< 0.1%

Unnamed: 14
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
7298 
유
2570 
<NA>
 
1
점자블록유무
 
1
BRLL_BLCK_ENNC_SE
 
1

Length

Max length17
Median length1
Mean length1.0024314
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 7298
73.9%
유 2570
 
26.0%
<NA> 1
 
< 0.1%
점자블록유무 1
 
< 0.1%
BRLL_BLCK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:11.830105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:11.946257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 7298
73.9%
유 2570
 
26.0%
na 1
 
< 0.1%
점자블록유무 1
 
< 0.1%
brll_blck_ennc_se 1
 
< 0.1%

Unnamed: 15
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
7376 
유
2492 
<NA>
 
1
경사로유무
 
1
SLPW__ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0019248
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 7376
74.7%
유 2492
 
25.2%
<NA> 1
 
< 0.1%
경사로유무 1
 
< 0.1%
SLPW__ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:12.086869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:12.221045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 7376
74.7%
유 2492
 
25.2%
na 1
 
< 0.1%
경사로유무 1
 
< 0.1%
slpw__ennc_se 1
 
< 0.1%

Unnamed: 16
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
8350 
유
1518 
<NA>
 
1
펜스유무
 
1
FENC_ENNC_SE
 
1

Length

Max length12
Median length1
Mean length1.0017222
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 8350
84.6%
유 1518
 
15.4%
<NA> 1
 
< 0.1%
펜스유무 1
 
< 0.1%
FENC_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:12.379130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:12.507586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 8350
84.6%
유 1518
 
15.4%
na 1
 
< 0.1%
펜스유무 1
 
< 0.1%
fenc_ennc_se 1
 
< 0.1%

Unnamed: 17
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
7408 
유
2460 
<NA>
 
1
버스정류장유무
 
1
BUS_STOPG_IPLA_ENNC_SE
 
1

Length

Max length22
Median length1
Mean length1.0030392
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 7408
75.0%
유 2460
 
24.9%
<NA> 1
 
< 0.1%
버스정류장유무 1
 
< 0.1%
BUS_STOPG_IPLA_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:12.638345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:12.768444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 7408
75.0%
유 2460
 
24.9%
na 1
 
< 0.1%
버스정류장유무 1
 
< 0.1%
bus_stopg_ipla_ennc_se 1
 
< 0.1%

Unnamed: 18
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:12.947681image/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%
2023-12-11T15:16:13.287621image/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 (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
7408 
유
2460 
<NA>
 
1
지하철유무
 
1
SUBWAY_ENNC_SE
 
1

Length

Max length14
Median length1
Mean length1.0020261
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 7408
75.0%
유 2460
 
24.9%
<NA> 1
 
< 0.1%
지하철유무 1
 
< 0.1%
SUBWAY_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:13.483370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:13.619281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 7408
75.0%
유 2460
 
24.9%
na 1
 
< 0.1%
지하철유무 1
 
< 0.1%
subway_ennc_se 1
 
< 0.1%

Unnamed: 20
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
무
5230 
유
4638 
<NA>
 
1
횡단보도유무
 
1
CRSLK_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0020261
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
무 5230
53.0%
유 4638
47.0%
<NA> 1
 
< 0.1%
횡단보도유무 1
 
< 0.1%
CRSLK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:13.786365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:13.907886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 5230
53.0%
유 4638
47.0%
na 1
 
< 0.1%
횡단보도유무 1
 
< 0.1%
crslk_ennc_se 1
 
< 0.1%

Unnamed: 21
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:14.065808image/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%
2023-12-11T15:16:14.405930image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:14.600078image/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%
2023-12-11T15:16:14.982905image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:15.160974image/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%
2023-12-11T15:16:15.485507image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:15.662482image/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%
2023-12-11T15:16:15.933527image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:16.122691image/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%
2023-12-11T15:16:16.425266image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:16.603208image/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%
2023-12-11T15:16:16.881477image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:17.043360image/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%
2023-12-11T15:16:17.365444image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:17.523160image/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%
2023-12-11T15:16:17.818860image/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
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
2종주거
3644 
3종주거
2731 
일반상업
1407 
1종주거
717 
준공업
533 
Other values (8)
839 

Length

Max length8
Median length4
Mean length3.8398339
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row용도구분
3rd rowPRPOS_NM
4th row2종주거
5th row2종주거

Common Values

ValueCountFrequency (%)
2종주거 3644
36.9%
3종주거 2731
27.7%
일반상업 1407
 
14.3%
1종주거 717
 
7.3%
준공업 533
 
5.4%
준주거 494
 
5.0%
녹지 279
 
2.8%
근린상업 34
 
0.3%
중심상업 25
 
0.3%
유통상업 4
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2023-12-11T15:16:17.973536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2종주거 3644
36.9%
3종주거 2731
27.7%
일반상업 1407
 
14.3%
1종주거 717
 
7.3%
준공업 533
 
5.4%
준주거 494
 
5.0%
녹지 279
 
2.8%
근린상업 34
 
0.3%
중심상업 25
 
0.3%
유통상업 4
 
< 0.1%
Other values (3) 3
 
< 0.1%

Unnamed: 30
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:18.159891image/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%
2023-12-11T15:16:18.544987image/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%
Missing9869
Missing (%)> 99.9%
Memory size77.2 KiB
2023-12-11T15:16:18.702986image/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%
2023-12-11T15:16:19.075818image/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

Distinct9850
Distinct (%)> 99.9%
Missing19
Missing (%)0.2%
Memory size77.2 KiB
2023-12-11T15:16:19.346220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.889464
Min length3

Characters and Unicode

Total characters117135
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

Unique9848 ?
Unique (%)> 99.9%

Sample

1st rowX좌표
2nd rowXCRD_LC
3rd row197049.74567
4th row196222.46838
5th row196423.97707
ValueCountFrequency (%)
193903.8765 2
 
< 0.1%
193396.32944 2
 
< 0.1%
193799.34078 1
 
< 0.1%
190632.0818 1
 
< 0.1%
191616.94487 1
 
< 0.1%
192340.71569 1
 
< 0.1%
192996.65411 1
 
< 0.1%
194291.82629 1
 
< 0.1%
194066.32319 1
 
< 0.1%
191908.20465 1
 
< 0.1%
Other values (9840) 9840
99.9%
2023-12-11T15:16:19.780377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14307
12.2%
1 14254
12.2%
0 12429
10.6%
9 12037
10.3%
8 9887
8.4%
. 9850
8.4%
6 9183
7.8%
3 9128
7.8%
5 8761
7.5%
7 8754
7.5%
Other values (9) 8545
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107275
91.6%
Other Punctuation 9850
 
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 14307
13.3%
1 14254
13.3%
0 12429
11.6%
9 12037
11.2%
8 9887
9.2%
6 9183
8.6%
3 9128
8.5%
5 8761
8.2%
7 8754
8.2%
4 8535
8.0%
Uppercase Letter
ValueCountFrequency (%)
X 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 (%)
. 9850
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117126
> 99.9%
Latin 7
 
< 0.1%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14307
12.2%
1 14254
12.2%
0 12429
10.6%
9 12037
10.3%
8 9887
8.4%
. 9850
8.4%
6 9183
7.8%
3 9128
7.8%
5 8761
7.5%
7 8754
7.5%
Other values (2) 8536
7.3%
Latin
ValueCountFrequency (%)
X 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 117133
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14307
12.2%
1 14254
12.2%
0 12429
10.6%
9 12037
10.3%
8 9887
8.4%
. 9850
8.4%
6 9183
7.8%
3 9128
7.8%
5 8761
7.5%
7 8754
7.5%
Other values (7) 8543
7.3%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Unnamed: 33
Text

Distinct9850
Distinct (%)> 99.9%
Missing19
Missing (%)0.2%
Memory size77.2 KiB
2023-12-11T15:16:20.039200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.885911
Min length3

Characters and Unicode

Total characters117100
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

Unique9848 ?
Unique (%)> 99.9%

Sample

1st rowY좌표
2nd rowYCRD_LC
3rd row456193.22472
4th row456497.4274
5th row455511.52968
ValueCountFrequency (%)
450719.50641 2
 
< 0.1%
450393.09452 2
 
< 0.1%
449453.34535 1
 
< 0.1%
445328.52829 1
 
< 0.1%
443367.92828 1
 
< 0.1%
441979.56774 1
 
< 0.1%
444717.63386 1
 
< 0.1%
447246.49575 1
 
< 0.1%
447481.10762 1
 
< 0.1%
444568.06339 1
 
< 0.1%
Other values (9840) 9840
99.9%
2023-12-11T15:16:20.430728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 23901
20.4%
5 13009
11.1%
. 9850
8.4%
6 9309
 
7.9%
2 9180
 
7.8%
3 9162
 
7.8%
1 8946
 
7.6%
8 8813
 
7.5%
7 8736
 
7.5%
9 8663
 
7.4%
Other values (9) 7531
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107240
91.6%
Other Punctuation 9850
 
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 23901
22.3%
5 13009
12.1%
6 9309
 
8.7%
2 9180
 
8.6%
3 9162
 
8.5%
1 8946
 
8.3%
8 8813
 
8.2%
7 8736
 
8.1%
9 8663
 
8.1%
0 7521
 
7.0%
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 (%)
. 9850
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117091
> 99.9%
Latin 7
 
< 0.1%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 23901
20.4%
5 13009
11.1%
. 9850
8.4%
6 9309
 
8.0%
2 9180
 
7.8%
3 9162
 
7.8%
1 8946
 
7.6%
8 8813
 
7.5%
7 8736
 
7.5%
9 8663
 
7.4%
Other values (2) 7522
 
6.4%
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 117098
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 23901
20.4%
5 13009
11.1%
. 9850
8.4%
6 9309
 
7.9%
2 9180
 
7.8%
3 9162
 
7.8%
1 8946
 
7.6%
8 8813
 
7.5%
7 8736
 
7.5%
9 8663
 
7.4%
Other values (7) 7529
 
6.4%
Hangul
ValueCountFrequency (%)
좌 1
50.0%
표 1
50.0%

Unnamed: 34
Text

Distinct4196
Distinct (%)42.6%
Missing19
Missing (%)0.2%
Memory size77.2 KiB
2023-12-11T15:16:20.689739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.99868
Min length5

Characters and Unicode

Total characters128063
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

Unique2297 ?
Unique (%)23.3%

Sample

1st row집계구코드
2nd rowSM_GU_CD
3rd row1101056030004
4th row1101056040001
5th row1101055010007
ValueCountFrequency (%)
1102055060001 79
 
0.8%
1101061040001 75
 
0.8%
1102052020001 60
 
0.6%
1101061020001 41
 
0.4%
1102059080001 37
 
0.4%
1102054070001 35
 
0.4%
1101061030002 29
 
0.3%
1102052010001 28
 
0.3%
1101063040001 27
 
0.3%
1119054050001 25
 
0.3%
Other values (4186) 9416
95.6%
2023-12-11T15:16:21.150501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51825
40.5%
1 33875
26.5%
2 10386
 
8.1%
5 6828
 
5.3%
6 5729
 
4.5%
3 5364
 
4.2%
7 4934
 
3.9%
4 4494
 
3.5%
8 2456
 
1.9%
9 2159
 
1.7%
Other values (12) 13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128050
> 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 51825
40.5%
1 33875
26.5%
2 10386
 
8.1%
5 6828
 
5.3%
6 5729
 
4.5%
3 5364
 
4.2%
7 4934
 
3.9%
4 4494
 
3.5%
8 2456
 
1.9%
9 2159
 
1.7%
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 128052
> 99.9%
Latin 6
 
< 0.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51825
40.5%
1 33875
26.5%
2 10386
 
8.1%
5 6828
 
5.3%
6 5729
 
4.5%
3 5364
 
4.2%
7 4934
 
3.9%
4 4494
 
3.5%
8 2456
 
1.9%
9 2159
 
1.7%
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 128058
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51825
40.5%
1 33875
26.5%
2 10386
 
8.1%
5 6828
 
5.3%
6 5729
 
4.5%
3 5364
 
4.2%
7 4934
 
3.9%
4 4494
 
3.5%
8 2456
 
1.9%
9 2159
 
1.7%
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 (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
2012
9868 
<NA>
 
1
년도
 
1
YEAR
 
1

Length

Max length4
Median length4
Mean length3.9997974
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row년도
3rd rowYEAR
4th row2012
5th row2012

Common Values

ValueCountFrequency (%)
2012 9868
> 99.9%
<NA> 1
 
< 0.1%
년도 1
 
< 0.1%
YEAR 1
 
< 0.1%

Length

2023-12-11T15:16:21.334696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:21.445643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2012 9868
> 99.9%
na 1
 
< 0.1%
년도 1
 
< 0.1%
year 1
 
< 0.1%

Unnamed: 36
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.2 KiB
본조사
9850 
<NA>
 
19
조사구분
 
1
EXAMIN_CLS
 
1

Length

Max length10
Median length3
Mean length3.0027353
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
본조사 9850
99.8%
<NA> 19
 
0.2%
조사구분 1
 
< 0.1%
EXAMIN_CLS 1
 
< 0.1%

Length

2023-12-11T15:16:21.568684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:21.704601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본조사 9850
99.8%
na 19
 
0.2%
조사구분 1
 
< 0.1%
examin_cls 1
 
< 0.1%

Sample

유동인구_조사지점정보_2012Unnamed: 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
301-001평창치안센터(파출소).1101011010562294<NA>35유유유가로수 보호대보도전용무무무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>197049.74567456193.2247211010560300042012본조사
401-002구기 빌딩앞(카리스).11010110105611012<NA>46유유유가로수보도전용무유무무<NA>무유<NA><NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196222.46838456497.427411010560400012012본조사
501-003신흥모피명품전문크리닝.11010110105512711<NA>38유유유가로수보도전용무유무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196423.97707455511.5296811010550100072012본조사
601-004우리농산물마트.110101101055942<NA>37유유유가로수자동차겸용유무무유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196315.80243455621.3826211010550200052012본조사
701-005세검정정류장110101101055920세검정길45유유유가로수보도전용무유유유<NA>유유<NA><NA><NA><NA><NA><NA><NA><NA>1종주거<NA><NA>196357.17125455680.825811010550100022012본조사
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유동인구_조사지점정보_2012Unnamed: 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
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