Overview

Dataset statistics

Number of variables37
Number of observations9853
Missing cells21988
Missing cells (%)6.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory296.0 B

Variable types

Text11
Categorical26

Dataset

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

Alerts

Unnamed: 9 is highly imbalanced (84.1%)Imbalance
Unnamed: 10 is highly imbalanced (56.8%)Imbalance
Unnamed: 11 is highly imbalanced (83.0%)Imbalance
Unnamed: 13 is highly imbalanced (52.3%)Imbalance
Unnamed: 14 is highly imbalanced (64.8%)Imbalance
Unnamed: 16 is highly imbalanced (73.2%)Imbalance
Unnamed: 17 is highly imbalanced (66.2%)Imbalance
Unnamed: 19 is highly imbalanced (84.1%)Imbalance
Unnamed: 20 is highly imbalanced (56.9%)Imbalance
Unnamed: 22 is highly imbalanced (91.4%)Imbalance
Unnamed: 23 is highly imbalanced (84.6%)Imbalance
Unnamed: 24 is highly imbalanced (81.3%)Imbalance
Unnamed: 25 is highly imbalanced (84.4%)Imbalance
Unnamed: 26 is highly imbalanced (69.6%)Imbalance
Unnamed: 27 is highly imbalanced (76.3%)Imbalance
Unnamed: 28 is highly imbalanced (62.2%)Imbalance
Unnamed: 30 is highly imbalanced (55.7%)Imbalance
Unnamed: 31 is highly imbalanced (60.7%)Imbalance
Unnamed: 35 is highly imbalanced (99.8%)Imbalance
Unnamed: 36 is highly imbalanced (99.8%)Imbalance
Unnamed: 6 has 2154 (21.9%) missing valuesMissing
Unnamed: 15 has 9851 (> 99.9%) missing valuesMissing
Unnamed: 18 has 9851 (> 99.9%) missing valuesMissing

Reproduction

Analysis started2023-12-11 06:16:28.051521
Analysis finished2023-12-11 06:16:31.119027
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct9852
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:31.458762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.3819529
Min length6

Characters and Unicode

Total characters62875
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

Unique9852 ?
Unique (%)100.0%

Sample

1st row조사지점코드
2nd rowEXAMIN_SPOT_CD
3rd row01-001
4th row01-002
5th row01-003
ValueCountFrequency (%)
01-006 1
 
< 0.1%
19-084 1
 
< 0.1%
19-096 1
 
< 0.1%
19-069 1
 
< 0.1%
19-076 1
 
< 0.1%
19-077 1
 
< 0.1%
19-078 1
 
< 0.1%
19-079 1
 
< 0.1%
19-080 1
 
< 0.1%
19-087 1
 
< 0.1%
Other values (9842) 9842
99.9%
2023-12-11T15:16:31.945997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10964
17.4%
- 9850
15.7%
1 9838
15.6%
2 9578
15.2%
3 5509
8.8%
4 3924
 
6.2%
5 2981
 
4.7%
8 2703
 
4.3%
6 2602
 
4.1%
9 2462
 
3.9%
Other values (20) 2464
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53005
84.3%
Dash Punctuation 9850
 
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 10964
20.7%
1 9838
18.6%
2 9578
18.1%
3 5509
10.4%
4 3924
 
7.4%
5 2981
 
5.6%
8 2703
 
5.1%
6 2602
 
4.9%
9 2462
 
4.6%
7 2444
 
4.6%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 9850
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62857
> 99.9%
Latin 12
 
< 0.1%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10964
17.4%
- 9850
15.7%
1 9838
15.7%
2 9578
15.2%
3 5509
8.8%
4 3924
 
6.2%
5 2981
 
4.7%
8 2703
 
4.3%
6 2602
 
4.1%
9 2462
 
3.9%
Other values (2) 2446
 
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 (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62869
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10964
17.4%
- 9850
15.7%
1 9838
15.6%
2 9578
15.2%
3 5509
8.8%
4 3924
 
6.2%
5 2981
 
4.7%
8 2703
 
4.3%
6 2602
 
4.1%
9 2462
 
3.9%
Other values (14) 2458
 
3.9%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Distinct9518
Distinct (%)96.6%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:32.222889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length10.689809
Min length2

Characters and Unicode

Total characters105316
Distinct characters974
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

Unique9304 ?
Unique (%)94.4%

Sample

1st row조사지점명
2nd rowEXAMIN_SPOT_NM
3rd row평창치안센터(파출소)
4th row말리브
5th row신흥모피명품전문크리닝 주변
ValueCountFrequency (%)
주변 8851
33.6%
467
 
1.8%
주택 292
 
1.1%
입구 137
 
0.5%
맞은편 131
 
0.5%
114
 
0.4%
아파트 105
 
0.4%
주차장 105
 
0.4%
빌라 99
 
0.4%
건너편 94
 
0.4%
Other values (10860) 15912
60.5%
2023-12-11T15:16:32.637288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16455
 
15.6%
9965
 
9.5%
8878
 
8.4%
1915
 
1.8%
1403
 
1.3%
1 1151
 
1.1%
952
 
0.9%
931
 
0.9%
878
 
0.8%
820
 
0.8%
Other values (964) 61968
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77991
74.1%
Space Separator 16457
 
15.6%
Decimal Number 5116
 
4.9%
Uppercase Letter 2371
 
2.3%
Lowercase Letter 1682
 
1.6%
Dash Punctuation 590
 
0.6%
Close Punctuation 474
 
0.5%
Open Punctuation 473
 
0.4%
Other Punctuation 132
 
0.1%
Modifier Symbol 11
 
< 0.1%
Other values (6) 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9965
 
12.8%
8878
 
11.4%
1915
 
2.5%
1403
 
1.8%
952
 
1.2%
931
 
1.2%
878
 
1.1%
820
 
1.1%
812
 
1.0%
768
 
1.0%
Other values (875) 50669
65.0%
Uppercase Letter
ValueCountFrequency (%)
S 250
 
10.5%
T 189
 
8.0%
A 175
 
7.4%
K 164
 
6.9%
C 158
 
6.7%
O 131
 
5.5%
G 131
 
5.5%
E 125
 
5.3%
I 111
 
4.7%
B 109
 
4.6%
Other values (16) 828
34.9%
Lowercase Letter
ValueCountFrequency (%)
e 191
11.4%
a 153
 
9.1%
o 150
 
8.9%
i 121
 
7.2%
t 115
 
6.8%
l 114
 
6.8%
r 113
 
6.7%
n 98
 
5.8%
s 90
 
5.4%
m 83
 
4.9%
Other values (16) 454
27.0%
Decimal Number
ValueCountFrequency (%)
1 1151
22.5%
2 789
15.4%
3 641
12.5%
0 590
11.5%
5 434
 
8.5%
4 388
 
7.6%
6 332
 
6.5%
7 297
 
5.8%
9 252
 
4.9%
8 242
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 69
52.3%
& 39
29.5%
/ 10
 
7.6%
@ 5
 
3.8%
? 4
 
3.0%
" 2
 
1.5%
* 1
 
0.8%
· 1
 
0.8%
: 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
| 2
40.0%
+ 1
20.0%
= 1
20.0%
~ 1
20.0%
Letter Number
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Space Separator
ValueCountFrequency (%)
16455
> 99.9%
  2
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 7
63.6%
^ 4
36.4%
Dash Punctuation
ValueCountFrequency (%)
- 590
100.0%
Close Punctuation
ValueCountFrequency (%)
) 474
100.0%
Open Punctuation
ValueCountFrequency (%)
( 473
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77954
74.0%
Common 23265
 
22.1%
Latin 4058
 
3.9%
Han 39
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9965
 
12.8%
8878
 
11.4%
1915
 
2.5%
1403
 
1.8%
952
 
1.2%
931
 
1.2%
878
 
1.1%
820
 
1.1%
812
 
1.0%
768
 
1.0%
Other values (840) 50632
65.0%
Latin
ValueCountFrequency (%)
S 250
 
6.2%
e 191
 
4.7%
T 189
 
4.7%
A 175
 
4.3%
K 164
 
4.0%
C 158
 
3.9%
a 153
 
3.8%
o 150
 
3.7%
O 131
 
3.2%
G 131
 
3.2%
Other values (45) 2366
58.3%
Han
ValueCountFrequency (%)
3
 
7.7%
2
 
5.1%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Other values (26) 26
66.7%
Common
ValueCountFrequency (%)
16455
70.7%
1 1151
 
4.9%
2 789
 
3.4%
3 641
 
2.8%
- 590
 
2.5%
0 590
 
2.5%
) 474
 
2.0%
( 473
 
2.0%
5 434
 
1.9%
4 388
 
1.7%
Other values (23) 1280
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77952
74.0%
ASCII 27311
 
25.9%
CJK 38
 
< 0.1%
None 5
 
< 0.1%
Number Forms 5
 
< 0.1%
Punctuation 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16455
60.3%
1 1151
 
4.2%
2 789
 
2.9%
3 641
 
2.3%
- 590
 
2.2%
0 590
 
2.2%
) 474
 
1.7%
( 473
 
1.7%
5 434
 
1.6%
4 388
 
1.4%
Other values (71) 5326
 
19.5%
Hangul
ValueCountFrequency (%)
9965
 
12.8%
8878
 
11.4%
1915
 
2.5%
1403
 
1.8%
952
 
1.2%
931
 
1.2%
878
 
1.1%
820
 
1.1%
812
 
1.0%
768
 
1.0%
Other values (839) 50630
65.0%
CJK
ValueCountFrequency (%)
3
 
7.9%
2
 
5.3%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Other values (25) 25
65.8%
None
ValueCountFrequency (%)
2
40.0%
  2
40.0%
· 1
20.0%
Number Forms
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Punctuation
ValueCountFrequency (%)
2
50.0%
2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

Unnamed: 2
Categorical

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
11230
 
665
11220
 
621
11110
 
607
11190
 
583
11240
 
554
Other values (23)
6823 

Length

Max length5
Median length5
Mean length4.9924896
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
 
6.2%
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) 4613
46.8%

Length

2023-12-11T15:16:32.775901image/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
 
6.2%
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) 4613
46.8%
Distinct413
Distinct (%)4.2%
Missing72
Missing (%)0.7%
Memory size77.1 KiB
2023-12-11T15:16:33.138515image/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%
2023-12-11T15:16:33.694092image/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 (%)
1
33.3%
1
33.3%
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 (%)
1
33.3%
1
33.3%
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 (%)
1
33.3%
1
33.3%
1
33.3%
Distinct1565
Distinct (%)16.0%
Missing54
Missing (%)0.5%
Memory size77.1 KiB
2023-12-11T15:16:34.110498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length2.7793652
Min length1

Characters and Unicode

Total characters27235
Distinct characters91
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique509 ?
Unique (%)5.2%

Sample

1st row주번지
2nd rowBUNJI
3rd row229
4th row110
5th row127
ValueCountFrequency (%)
1 110
 
1.1%
0 55
 
0.6%
5 53
 
0.5%
50 50
 
0.5%
없음 49
 
0.5%
35 49
 
0.5%
45 47
 
0.5%
10 46
 
0.5%
17 45
 
0.5%
18 43
 
0.4%
Other values (1560) 9258
94.4%
2023-12-11T15:16:34.682252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4588
16.8%
2 3093
11.4%
3 2965
10.9%
4 2651
9.7%
5 2610
9.6%
6 2458
9.0%
7 2272
8.3%
0 2196
8.1%
9 2031
7.5%
8 1973
7.2%
Other values (81) 398
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26837
98.5%
Other Letter 219
 
0.8%
Dash Punctuation 162
 
0.6%
Space Separator 8
 
< 0.1%
Uppercase Letter 7
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
49
22.4%
49
22.4%
20
 
9.1%
5
 
2.3%
5
 
2.3%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
Other values (59) 76
34.7%
Decimal Number
ValueCountFrequency (%)
1 4588
17.1%
2 3093
11.5%
3 2965
11.0%
4 2651
9.9%
5 2610
9.7%
6 2458
9.2%
7 2272
8.5%
0 2196
8.2%
9 2031
7.6%
8 1973
7.4%
Uppercase Letter
ValueCountFrequency (%)
X 1
14.3%
K 1
14.3%
B 1
14.3%
U 1
14.3%
N 1
14.3%
J 1
14.3%
I 1
14.3%
Space Separator
ValueCountFrequency (%)
7
87.5%
  1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
m 1
50.0%
o 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27007
99.2%
Hangul 219
 
0.8%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
49
22.4%
49
22.4%
20
 
9.1%
5
 
2.3%
5
 
2.3%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
Other values (59) 76
34.7%
Common
ValueCountFrequency (%)
1 4588
17.0%
2 3093
11.5%
3 2965
11.0%
4 2651
9.8%
5 2610
9.7%
6 2458
9.1%
7 2272
8.4%
0 2196
8.1%
9 2031
7.5%
8 1973
7.3%
Other values (3) 170
 
0.6%
Latin
ValueCountFrequency (%)
X 1
11.1%
m 1
11.1%
K 1
11.1%
o 1
11.1%
B 1
11.1%
U 1
11.1%
N 1
11.1%
J 1
11.1%
I 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27015
99.2%
Hangul 218
 
0.8%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4588
17.0%
2 3093
11.4%
3 2965
11.0%
4 2651
9.8%
5 2610
9.7%
6 2458
9.1%
7 2272
8.4%
0 2196
8.1%
9 2031
7.5%
8 1973
7.3%
Other values (11) 178
 
0.7%
Hangul
ValueCountFrequency (%)
49
22.5%
49
22.5%
20
 
9.2%
5
 
2.3%
5
 
2.3%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
3
 
1.4%
Other values (58) 75
34.4%
None
ValueCountFrequency (%)
  1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct362
Distinct (%)3.7%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:35.042719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4812221
Min length1

Characters and Unicode

Total characters14593
Distinct characters50
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)1.5%

Sample

1st row부번지
2nd rowBUBUN
3rd row4
4th row12
5th row11
ValueCountFrequency (%)
0 2211
22.4%
1 930
 
9.4%
2 495
 
5.0%
3 394
 
4.0%
4 372
 
3.8%
5 346
 
3.5%
7 268
 
2.7%
6 263
 
2.7%
8 217
 
2.2%
10 209
 
2.1%
Other values (353) 4148
42.1%
2023-12-11T15:16:35.583359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3253
22.3%
0 2851
19.5%
2 1882
12.9%
3 1377
9.4%
4 1170
 
8.0%
5 1041
 
7.1%
6 820
 
5.6%
7 780
 
5.3%
8 723
 
5.0%
9 636
 
4.4%
Other values (40) 60
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14533
99.6%
Other Letter 42
 
0.3%
Other Punctuation 6
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
11.9%
5
 
11.9%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (20) 20
47.6%
Decimal Number
ValueCountFrequency (%)
1 3253
22.4%
0 2851
19.6%
2 1882
12.9%
3 1377
9.5%
4 1170
 
8.1%
5 1041
 
7.2%
6 820
 
5.6%
7 780
 
5.4%
8 723
 
5.0%
9 636
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
U 2
33.3%
B 2
33.3%
N 1
16.7%
G 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 1
 
16.7%
/ 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14545
99.7%
Hangul 42
 
0.3%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
11.9%
5
 
11.9%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (20) 20
47.6%
Common
ValueCountFrequency (%)
1 3253
22.4%
0 2851
19.6%
2 1882
12.9%
3 1377
9.5%
4 1170
 
8.0%
5 1041
 
7.2%
6 820
 
5.6%
7 780
 
5.4%
8 723
 
5.0%
9 636
 
4.4%
Other values (6) 12
 
0.1%
Latin
ValueCountFrequency (%)
U 2
33.3%
B 2
33.3%
N 1
16.7%
G 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14551
99.7%
Hangul 42
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3253
22.4%
0 2851
19.6%
2 1882
12.9%
3 1377
9.5%
4 1170
 
8.0%
5 1041
 
7.2%
6 820
 
5.6%
7 780
 
5.4%
8 723
 
5.0%
9 636
 
4.4%
Other values (10) 18
 
0.1%
Hangul
ValueCountFrequency (%)
5
 
11.9%
5
 
11.9%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (20) 20
47.6%

Unnamed: 6
Text

MISSING 

Distinct2369
Distinct (%)30.8%
Missing2154
Missing (%)21.9%
Memory size77.1 KiB
2023-12-11T15:16:36.003402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length3.9831147
Min length1

Characters and Unicode

Total characters30666
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

Unique1293 ?
Unique (%)16.8%

Sample

1st row도로명
2nd rowROAD_NM
3rd row세검정길
4th row세검정길
5th row세검정길
ValueCountFrequency (%)
없음 896
 
10.7%
조사표 66
 
0.8%
구로동길 54
 
0.6%
남부순환로 54
 
0.6%
한천로 52
 
0.6%
동1로 43
 
0.5%
조사표에 43
 
0.5%
망우로 41
 
0.5%
미기재 40
 
0.5%
강남대로 38
 
0.5%
Other values (2390) 7062
84.2%
2023-12-11T15:16:36.669976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4483
 
14.6%
2312
 
7.5%
943
 
3.1%
932
 
3.0%
858
 
2.8%
691
 
2.3%
1 555
 
1.8%
402
 
1.3%
353
 
1.2%
332
 
1.1%
Other values (472) 18805
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28151
91.8%
Decimal Number 1735
 
5.7%
Space Separator 691
 
2.3%
Other Punctuation 28
 
0.1%
Dash Punctuation 17
 
0.1%
Open Punctuation 16
 
0.1%
Close Punctuation 16
 
0.1%
Uppercase Letter 9
 
< 0.1%
Math Symbol 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4483
 
15.9%
2312
 
8.2%
943
 
3.3%
932
 
3.3%
858
 
3.0%
402
 
1.4%
353
 
1.3%
332
 
1.2%
305
 
1.1%
293
 
1.0%
Other values (443) 16938
60.2%
Decimal Number
ValueCountFrequency (%)
1 555
32.0%
2 324
18.7%
3 253
14.6%
4 173
 
10.0%
5 160
 
9.2%
6 105
 
6.1%
7 61
 
3.5%
9 46
 
2.7%
8 37
 
2.1%
0 21
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
11.1%
T 1
11.1%
G 1
11.1%
A 1
11.1%
O 1
11.1%
R 1
11.1%
D 1
11.1%
N 1
11.1%
M 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 21
75.0%
, 6
 
21.4%
& 1
 
3.6%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28149
91.8%
Common 2506
 
8.2%
Latin 9
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4483
 
15.9%
2312
 
8.2%
943
 
3.4%
932
 
3.3%
858
 
3.0%
402
 
1.4%
353
 
1.3%
332
 
1.2%
305
 
1.1%
293
 
1.0%
Other values (442) 16936
60.2%
Common
ValueCountFrequency (%)
691
27.6%
1 555
22.1%
2 324
12.9%
3 253
 
10.1%
4 173
 
6.9%
5 160
 
6.4%
6 105
 
4.2%
7 61
 
2.4%
9 46
 
1.8%
8 37
 
1.5%
Other values (10) 101
 
4.0%
Latin
ValueCountFrequency (%)
K 1
11.1%
T 1
11.1%
G 1
11.1%
A 1
11.1%
O 1
11.1%
R 1
11.1%
D 1
11.1%
N 1
11.1%
M 1
11.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28146
91.8%
ASCII 2515
 
8.2%
Compat Jamo 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4483
 
15.9%
2312
 
8.2%
943
 
3.4%
932
 
3.3%
858
 
3.0%
402
 
1.4%
353
 
1.3%
332
 
1.2%
305
 
1.1%
293
 
1.0%
Other values (440) 16933
60.2%
ASCII
ValueCountFrequency (%)
691
27.5%
1 555
22.1%
2 324
12.9%
3 253
 
10.1%
4 173
 
6.9%
5 160
 
6.4%
6 105
 
4.2%
7 61
 
2.4%
9 46
 
1.8%
8 37
 
1.5%
Other values (19) 110
 
4.4%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
2
100.0%

Unnamed: 7
Categorical

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
3
2264 
2
1921 
4
1844 
5
1318 
6
846 
Other values (20)
1660 

Length

Max length8
Median length1
Mean length1.0229372
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
3 2264
23.0%
2 1921
19.5%
4 1844
18.7%
5 1318
13.4%
6 846
 
8.6%
7 514
 
5.2%
1 505
 
5.1%
8 313
 
3.2%
10 113
 
1.1%
9 112
 
1.1%
Other values (15) 103
 
1.0%

Length

2023-12-11T15:16:36.869885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 2264
23.0%
2 1921
19.5%
4 1844
18.7%
5 1318
13.4%
6 846
 
8.6%
7 514
 
5.2%
1 505
 
5.1%
8 313
 
3.2%
10 113
 
1.1%
9 112
 
1.1%
Other values (15) 103
 
1.0%

Unnamed: 8
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
1
4490 
2
1604 
4
1431 
6
924 
8
 
417
Other values (13)
987 

Length

Max length6
Median length1
Mean length1.01837
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 4490
45.6%
2 1604
 
16.3%
4 1431
 
14.5%
6 924
 
9.4%
8 417
 
4.2%
5 287
 
2.9%
3 250
 
2.5%
7 219
 
2.2%
10 114
 
1.2%
9 57
 
0.6%
Other values (8) 60
 
0.6%

Length

2023-12-11T15:16:37.036896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 4490
45.6%
2 1604
 
16.3%
4 1431
 
14.5%
6 924
 
9.4%
8 417
 
4.2%
5 287
 
2.9%
3 250
 
2.5%
7 219
 
2.2%
10 114
 
1.2%
9 57
 
0.6%
Other values (8) 60
 
0.6%

Unnamed: 9
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
9164 
 
686
<NA>
 
1
버스차로유무
 
1
BUS_CARTRK_ENNC_SE
 
1

Length

Max length18
Median length1
Mean length1.0025373
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
9164
93.0%
686
 
7.0%
<NA> 1
 
< 0.1%
버스차로유무 1
 
< 0.1%
BUS_CARTRK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:37.203212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:37.345713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9164
93.0%
686
 
7.0%
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 size77.1 KiB
5153 
4697 
<NA>
 
1
중앙선여부
 
1
CTLN_AT_SE
 
1

Length

Max length10
Median length1
Mean length1.0016239
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
5153
52.3%
4697
47.7%
<NA> 1
 
< 0.1%
중앙선여부 1
 
< 0.1%
CTLN_AT_SE 1
 
< 0.1%

Length

2023-12-11T15:16:37.494307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:37.618015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5153
52.3%
4697
47.7%
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 size77.1 KiB
9092 
 
758
<NA>
 
1
장애물유무
 
1
OBSTC_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0019283
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
9092
92.3%
758
 
7.7%
<NA> 1
 
< 0.1%
장애물유무 1
 
< 0.1%
OBSTC_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:38.015349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:38.123176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9092
92.3%
758
 
7.7%
na 1
 
< 0.1%
장애물유무 1
 
< 0.1%
obstc_ennc_se 1
 
< 0.1%

Unnamed: 12
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
기타
2689 
가로수
2563 
가로등기둥
1658 
상가고정장애물 등
874 
<NA>
759 
Other values (15)
1310 

Length

Max length12
Median length9
Mean length3.754491
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2689
27.3%
가로수 2563
26.0%
가로등기둥 1658
16.8%
상가고정장애물 등 874
 
8.9%
<NA> 759
 
7.7%
기둥 535
 
5.4%
신호제어기 158
 
1.6%
쓰레기통 104
 
1.1%
가로등 보호대 103
 
1.0%
도로표지판 97
 
1.0%
Other values (10) 313
 
3.2%

Length

2023-12-11T15:16:38.249576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 2689
24.8%
가로수 2563
23.7%
가로등기둥 1658
15.3%
상가고정장애물 874
 
8.1%
874
 
8.1%
na 759
 
7.0%
기둥 535
 
4.9%
신호제어기 158
 
1.5%
쓰레기통 104
 
1.0%
가로등 103
 
1.0%
Other values (12) 513
 
4.7%

Unnamed: 13
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
보도전용
5396 
보도차도겸용
3929 
자전거겸용
 
525
<NA>
 
1
보행도로구분
 
1

Length

Max length12
Median length4
Mean length4.8518218
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 5396
54.8%
보도차도겸용 3929
39.9%
자전거겸용 525
 
5.3%
<NA> 1
 
< 0.1%
보행도로구분 1
 
< 0.1%
WALK_ROAD_SE 1
 
< 0.1%

Length

2023-12-11T15:16:38.419924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:38.552066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보도전용 5396
54.8%
보도차도겸용 3929
39.9%
자전거겸용 525
 
5.3%
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 size77.1 KiB
7370 
2480 
<NA>
 
1
점자블록유무
 
1
BRLL_BLCK_ENNC_SE
 
1

Length

Max length17
Median length1
Mean length1.0024358
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
7370
74.8%
2480
 
25.2%
<NA> 1
 
< 0.1%
점자블록유무 1
 
< 0.1%
BRLL_BLCK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:38.725522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:38.866601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7370
74.8%
2480
 
25.2%
na 1
 
< 0.1%
점자블록유무 1
 
< 0.1%
brll_blck_ennc_se 1
 
< 0.1%

Unnamed: 15
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9851
Missing (%)> 99.9%
Memory size77.1 KiB
2023-12-11T15:16:39.022238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9
Min length5

Characters and Unicode

Total characters18
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 row경사로유무
2nd rowSLPW__ENNC_SE
ValueCountFrequency (%)
경사로유무 1
50.0%
slpw__ennc_se 1
50.0%
2023-12-11T15:16:39.416885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 3
16.7%
S 2
11.1%
E 2
11.1%
N 2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
L 1
 
5.6%
Other values (3) 3
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10
55.6%
Other Letter 5
27.8%
Connector Punctuation 3
 
16.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
E 2
20.0%
N 2
20.0%
L 1
10.0%
P 1
10.0%
W 1
10.0%
C 1
10.0%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
55.6%
Hangul 5
27.8%
Common 3
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 2
20.0%
E 2
20.0%
N 2
20.0%
L 1
10.0%
P 1
10.0%
W 1
10.0%
C 1
10.0%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Common
ValueCountFrequency (%)
_ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
72.2%
Hangul 5
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 3
23.1%
S 2
15.4%
E 2
15.4%
N 2
15.4%
L 1
 
7.7%
P 1
 
7.7%
W 1
 
7.7%
C 1
 
7.7%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Unnamed: 16
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
8337 
1513 
<NA>
 
1
펜스유무
 
1
FENC_ENNC_SE
 
1

Length

Max length12
Median length1
Mean length1.0017254
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
8337
84.6%
1513
 
15.4%
<NA> 1
 
< 0.1%
펜스유무 1
 
< 0.1%
FENC_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:39.552648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:39.675779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8337
84.6%
1513
 
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 size77.1 KiB
7566 
2284 
<NA>
 
1
버스정류장유무
 
1
BUS_STOPG_IPLA_ENNC_SE
 
1

Length

Max length22
Median length1
Mean length1.0030448
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
7566
76.8%
2284
 
23.2%
<NA> 1
 
< 0.1%
버스정류장유무 1
 
< 0.1%
BUS_STOPG_IPLA_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:39.798428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:39.923795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7566
76.8%
2284
 
23.2%
na 1
 
< 0.1%
버스정류장유무 1
 
< 0.1%
bus_stopg_ipla_ennc_se 1
 
< 0.1%

Unnamed: 18
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9851
Missing (%)> 99.9%
Memory size77.1 KiB
2023-12-11T15:16:40.079586image/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%
2023-12-11T15:16:40.435987image/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%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
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 (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
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 (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
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 (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 19
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
9164 
 
686
<NA>
 
1
지하철유무
 
1
SUBWAY_ENNC_SE
 
1

Length

Max length14
Median length1
Mean length1.0020298
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
9164
93.0%
686
 
7.0%
<NA> 1
 
< 0.1%
지하철유무 1
 
< 0.1%
SUBWAY_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:40.645911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:40.802012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9164
93.0%
686
 
7.0%
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 size77.1 KiB
5291 
4559 
<NA>
 
1
횡단보도유무
 
1
CRSLK_ENNC_SE
 
1

Length

Max length13
Median length1
Mean length1.0020298
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
5291
53.7%
4559
46.3%
<NA> 1
 
< 0.1%
횡단보도유무 1
 
< 0.1%
CRSLK_ENNC_SE 1
 
< 0.1%

Length

2023-12-11T15:16:40.929460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:41.053011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5291
53.7%
4559
46.3%
na 1
 
< 0.1%
횡단보도유무 1
 
< 0.1%
crslk_ennc_se 1
 
< 0.1%

Unnamed: 21
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
유형3
3459 
유형7
2758 
유형2
2644 
유형4
 
274
유형9
 
186
Other values (7)
532 

Length

Max length13
Median length3
Mean length3.0012179
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row보도형태
3rd rowFTPTH_STLE_CN
4th row유형2
5th row유형2

Common Values

ValueCountFrequency (%)
유형3 3459
35.1%
유형7 2758
28.0%
유형2 2644
26.8%
유형4 274
 
2.8%
유형9 186
 
1.9%
유형1 158
 
1.6%
유형6 152
 
1.5%
유형5 123
 
1.2%
유형8 96
 
1.0%
<NA> 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2023-12-11T15:16:41.178408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
유형3 3459
35.1%
유형7 2758
28.0%
유형2 2644
26.8%
유형4 274
 
2.8%
유형9 186
 
1.9%
유형1 158
 
1.6%
유형6 152
 
1.5%
유형5 123
 
1.2%
유형8 96
 
1.0%
na 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Unnamed: 22
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
9494 
역삼1동
 
104
동대문
 
47
시청인근
 
40
이태원
 
33
Other values (11)
 
135

Length

Max length17
Median length4
Mean length3.9875165
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row글로벌존지역명
3rd rowGLOBAL_ZN_AREA_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9494
96.4%
역삼1동 104
 
1.1%
동대문 47
 
0.5%
시청인근 40
 
0.4%
이태원 33
 
0.3%
서래마을 31
 
0.3%
명동 21
 
0.2%
남대문 19
 
0.2%
이촌 16
 
0.2%
강남테헤란로 16
 
0.2%
Other values (6) 32
 
0.3%

Length

2023-12-11T15:16:41.324173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9494
96.4%
역삼1동 104
 
1.1%
동대문 47
 
0.5%
시청인근 40
 
0.4%
이태원 33
 
0.3%
서래마을 31
 
0.3%
명동 21
 
0.2%
남대문 19
 
0.2%
이촌 16
 
0.2%
강남테헤란로 16
 
0.2%
Other values (6) 32
 
0.3%

Unnamed: 23
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
9080 
관악구
 
76
노원구
 
72
동대문구
 
62
구로구
 
58
Other values (23)
 
505

Length

Max length14
Median length4
Mean length3.9336243
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row주거지역명
3rd rowRESIDE_AREA_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9080
92.2%
관악구 76
 
0.8%
노원구 72
 
0.7%
동대문구 62
 
0.6%
구로구 58
 
0.6%
강북구 57
 
0.6%
성북구 46
 
0.5%
송파구 33
 
0.3%
서대문구 29
 
0.3%
광진구 29
 
0.3%
Other values (18) 311
 
3.2%

Length

2023-12-11T15:16:41.498424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9080
92.2%
관악구 76
 
0.8%
노원구 72
 
0.7%
동대문구 62
 
0.6%
구로구 58
 
0.6%
강북구 57
 
0.6%
성북구 46
 
0.5%
송파구 33
 
0.3%
서대문구 29
 
0.3%
광진구 29
 
0.3%
Other values (18) 311
 
3.2%

Unnamed: 24
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
9119 
동북권
 
264
서북권
 
233
동남권
 
155
서남권
 
80
Other values (2)
 
2

Length

Max length14
Median length4
Mean length3.9268243
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row지역중심명
3rd rowAREA_CENTER_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9119
92.6%
동북권 264
 
2.7%
서북권 233
 
2.4%
동남권 155
 
1.6%
서남권 80
 
0.8%
지역중심명 1
 
< 0.1%
AREA_CENTER_NM 1
 
< 0.1%

Length

2023-12-11T15:16:41.662683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:41.818409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9119
92.6%
동북권 264
 
2.7%
서북권 233
 
2.4%
동남권 155
 
1.6%
서남권 80
 
0.8%
지역중심명 1
 
< 0.1%
area_center_nm 1
 
< 0.1%

Unnamed: 25
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
9119 
중화역
 
71
신촌역
 
63
미아삼거리역
 
60
길동역
 
53
Other values (16)
 
487

Length

Max length21
Median length4
Mean length3.94966
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row지역중심상세명
3rd rowAREA_CENTER_DETAIL_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9119
92.6%
중화역 71
 
0.7%
신촌역 63
 
0.6%
미아삼거리역 60
 
0.6%
길동역 53
 
0.5%
마포역 50
 
0.5%
목동역 49
 
0.5%
공덕역 47
 
0.5%
노원역 45
 
0.5%
사당역 45
 
0.5%
Other values (11) 251
 
2.5%

Length

2023-12-11T15:16:42.014333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9119
92.6%
중화역 71
 
0.7%
신촌역 63
 
0.6%
미아삼거리역 60
 
0.6%
길동역 53
 
0.5%
마포역 50
 
0.5%
목동역 49
 
0.5%
공덕역 47
 
0.5%
노원역 45
 
0.5%
사당역 45
 
0.5%
Other values (11) 251
 
2.5%

Unnamed: 26
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
8472 
동북권
 
536
서남권
 
383
동남권
 
273
서북권
 
187
Other values (2)
 
2

Length

Max length15
Median length4
Mean length3.8612605
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row지구중심명
3rd rowDSTRC_CENTER_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8472
86.0%
동북권 536
 
5.4%
서남권 383
 
3.9%
동남권 273
 
2.8%
서북권 187
 
1.9%
지구중심명 1
 
< 0.1%
DSTRC_CENTER_NM 1
 
< 0.1%

Length

2023-12-11T15:16:42.165014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:42.305156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8472
86.0%
동북권 536
 
5.4%
서남권 383
 
3.9%
동남권 273
 
2.8%
서북권 187
 
1.9%
지구중심명 1
 
< 0.1%
dstrc_center_nm 1
 
< 0.1%

Unnamed: 27
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
8472 
군자역
 
61
수유역
 
59
가락시장역, 문정역
 
58
건대입구역
 
58
Other values (43)
1145 

Length

Max length19
Median length4
Mean length3.9783822
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row지구중심상세내용
3rd rowDSTRC_CENTER_DETAIL
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8472
86.0%
군자역 61
 
0.6%
수유역 59
 
0.6%
가락시장역, 문정역 58
 
0.6%
건대입구역 58
 
0.6%
쌍문역 57
 
0.6%
돌곶이역 52
 
0.5%
금호역 44
 
0.4%
불광역 43
 
0.4%
응암역 43
 
0.4%
Other values (38) 906
 
9.2%

Length

2023-12-11T15:16:42.476509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8472
85.5%
문정역 87
 
0.9%
군자역 61
 
0.6%
수유역 59
 
0.6%
가락시장역 58
 
0.6%
건대입구역 58
 
0.6%
쌍문역 57
 
0.6%
돌곶이역 52
 
0.5%
금호역 44
 
0.4%
불광역 43
 
0.4%
Other values (38) 920
 
9.3%

Unnamed: 28
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
8036 
영동부도심
 
714
도심
 
701
용산부도심
 
400
도심부도심지역명
 
1

Length

Max length21
Median length4
Mean length3.9729017
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row도심부도심지역명
3rd rowCDCT_SUB_CDCT_AREA_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8036
81.6%
영동부도심 714
 
7.2%
도심 701
 
7.1%
용산부도심 400
 
4.1%
도심부도심지역명 1
 
< 0.1%
CDCT_SUB_CDCT_AREA_NM 1
 
< 0.1%

Length

2023-12-11T15:16:42.656002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:42.803500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8036
81.6%
영동부도심 714
 
7.2%
도심 701
 
7.1%
용산부도심 400
 
4.1%
도심부도심지역명 1
 
< 0.1%
cdct_sub_cdct_area_nm 1
 
< 0.1%

Unnamed: 29
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
2종주거
3640 
3종주거
2722 
일반상업
1407 
1종주거
714 
준공업
532 
Other values (8)
838 

Length

Max length8
Median length4
Mean length3.8397442
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
2종주거 3640
36.9%
3종주거 2722
27.6%
일반상업 1407
 
14.3%
1종주거 714
 
7.2%
준공업 532
 
5.4%
준주거 493
 
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

2023-12-11T15:16:42.955152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2종주거 3640
36.9%
3종주거 2722
27.6%
일반상업 1407
 
14.3%
1종주거 714
 
7.2%
준공업 532
 
5.4%
준주거 493
 
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
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
7299 
다세대다가구
1648 
다세대+소규모아파트단지
 
683
아파트단지밀집
 
221
거주유형구분
 
1

Length

Max length12
Median length4
Mean length4.9573734
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row거주유형구분
3rd rowRESIDE_TY_SE
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7299
74.1%
다세대다가구 1648
 
16.7%
다세대+소규모아파트단지 683
 
6.9%
아파트단지밀집 221
 
2.2%
거주유형구분 1
 
< 0.1%
RESIDE_TY_SE 1
 
< 0.1%

Length

2023-12-11T15:16:43.140717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:43.315075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7299
74.1%
다세대다가구 1648
 
16.7%
다세대+소규모아파트단지 683
 
6.9%
아파트단지밀집 221
 
2.2%
거주유형구분 1
 
< 0.1%
reside_ty_se 1
 
< 0.1%

Unnamed: 31
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
<NA>
7299 
역세권-용도혼합
1947 
비역세권-용도순화
 
408
비역세권-용도혼합
 
152
역세권-용도순화
 
45
Other values (2)
 
2

Length

Max length9
Median length4
Mean length5.0934741
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row입지유형명
3rd rowLCT_TY_NM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7299
74.1%
역세권-용도혼합 1947
 
19.8%
비역세권-용도순화 408
 
4.1%
비역세권-용도혼합 152
 
1.5%
역세권-용도순화 45
 
0.5%
입지유형명 1
 
< 0.1%
LCT_TY_NM 1
 
< 0.1%

Length

2023-12-11T15:16:43.488871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:43.662678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7299
74.1%
역세권-용도혼합 1947
 
19.8%
비역세권-용도순화 408
 
4.1%
비역세권-용도혼합 152
 
1.5%
역세권-용도순화 45
 
0.5%
입지유형명 1
 
< 0.1%
lct_ty_nm 1
 
< 0.1%
Distinct9850
Distinct (%)> 99.9%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:43.970640image/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%
200024.37781 1
 
< 0.1%
191798.50159 1
 
< 0.1%
190374.64255 1
 
< 0.1%
191616.94487 1
 
< 0.1%
190692.98599 1
 
< 0.1%
190724.05827 1
 
< 0.1%
194291.82629 1
 
< 0.1%
194066.32319 1
 
< 0.1%
Other values (9840) 9840
99.9%
2023-12-11T15:16:44.457084image/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 (%)
1
50.0%
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 (%)
1
50.0%
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 (%)
1
50.0%
1
50.0%
Distinct9850
Distinct (%)> 99.9%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:44.807404image/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%
444208.27941 1
 
< 0.1%
445574.93212 1
 
< 0.1%
447438.85806 1
 
< 0.1%
443367.92828 1
 
< 0.1%
449100.29542 1
 
< 0.1%
444860.49084 1
 
< 0.1%
447246.49575 1
 
< 0.1%
447481.10762 1
 
< 0.1%
Other values (9840) 9840
99.9%
2023-12-11T15:16:45.288039image/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 (%)
1
50.0%
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 (%)
1
50.0%
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 (%)
1
50.0%
1
50.0%
Distinct4196
Distinct (%)42.6%
Missing1
Missing (%)< 0.1%
Memory size77.1 KiB
2023-12-11T15:16:45.540950image/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%
1101053030003 25
 
0.3%
Other values (4186) 9416
95.6%
2023-12-11T15:16:45.980415image/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 (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
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 (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
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 (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Unnamed: 35
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.1 KiB
2009
9850 
<NA>
 
1
년도
 
1
YEAR
 
1

Length

Max length4
Median length4
Mean length3.999797
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row년도
3rd rowYEAR
4th row2009
5th row2009

Common Values

ValueCountFrequency (%)
2009 9850
> 99.9%
<NA> 1
 
< 0.1%
년도 1
 
< 0.1%
YEAR 1
 
< 0.1%

Length

2023-12-11T15:16:46.160661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:46.296727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2009 9850
> 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 size77.1 KiB
본조사
9850 
<NA>
 
1
조사구분
 
1
EXAMIN_CLS
 
1

Length

Max length10
Median length3
Mean length3.0009134
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
본조사 9850
> 99.9%
<NA> 1
 
< 0.1%
조사구분 1
 
< 0.1%
EXAMIN_CLS 1
 
< 0.1%

Length

2023-12-11T15:16:46.415416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:16:46.529477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본조사 9850
> 99.9%
na 1
 
< 0.1%
조사구분 1
 
< 0.1%
examin_cls 1
 
< 0.1%

Sample

유동인구_조사지점정보_2009Unnamed: 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>35가로등 보호대보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>197049.74567456193.2247211010560300042009본조사
401-002말리브11010110105611012<NA>46가로수보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196222.46838456497.427411010560400012009본조사
501-003신흥모피명품전문크리닝 주변11010110105512711<NA>38가로수보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196423.97707455511.5296811010550100072009본조사
601-004GS25110101101055942<NA>37가로수자전거겸용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>196315.80243455621.3826211010550200052009본조사
701-005세검정정류장 주변110101101055920세검정길45가로수보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>1종주거<NA><NA>196357.17125455680.825811010550100022009본조사
801-006부흥문구사 입구 주변1101011010563301세검정길35가로수보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>197050.37285456228.2330111010560200112009본조사
901-007국민대학교 삼림과학대학 실습장110101101056<NA>0세검정길34가로수보도전용<NA><NA>유형2<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>197662.28452456614.7683911010560200082009본조사
유동인구_조사지점정보_2009Unnamed: 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
984325-834굳웰잉크전문점 주변11250112506555314없음51상가고정장애물 등보도전용<NA><NA>유형3<NA><NA><NA><NA><NA><NA><NA>3종주거<NA><NA>210747.04449447879.4727811250650200012009본조사
984425-840보광당 주변1125011250556434샘터길33가로수보도전용<NA><NA>유형7<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>213626.92082451109.3547911250550300122009본조사
984525-841묘곡초등학교 주변1125011250554980샘터길32가로수보도전용<NA><NA>유형7<NA><NA><NA><NA>동남권고덕역<NA>2종주거아파트단지밀집역세권-용도혼합213481.3297451069.8026711250550300072009본조사
984625-843고덕 IPARK 주변11250112505510815<NA>43가로등 보호대자전거겸용<NA><NA>유형7<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>213691.18468451179.0441811250550300022009본조사
984725-844성내1동 농협중앙회 주변1125011250654510성내중앙길92상가고정장애물 등보도차도겸용<NA><NA>유형7<NA><NA><NA><NA><NA><NA><NA>3종주거<NA><NA>210668.19575447770.6262911250650200012009본조사
984825-845성내1동 IBK 기업은행 주변1125011250655511구청앞길54가로수보도전용<NA><NA>유형7<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>210851.42279447750.5727411250650200012009본조사
984925-846geo (지오) 주변11250112506555513성내중앙길92상가고정장애물 등보도차도겸용<NA><NA>유형3<NA><NA><NA><NA><NA><NA><NA>3종주거<NA><NA>210749.70303447723.4892711250650200012009본조사
985025-847대명 복 전문점 주변1125011250654549구청앞길24가로등기둥보도전용<NA><NA>유형3<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>210797.80696447619.9928611250650300052009본조사
985125-848장원삼계탕 주변1125011250655585성내중앙길92가로등기둥보도차도겸용<NA><NA>유형3<NA><NA><NA><NA><NA><NA><NA>2종주거<NA><NA>210921.63224447637.3105811250650300012009본조사
985225-849먹골사철탕 주변11250112506532019없음32가로등기둥보도전용<NA><NA>유형7<NA><NA><NA><NA><NA><NA><NA>3종주거<NA><NA>210748.02372447975.4904411250650100062009본조사