Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2023-04-14
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 1 (2.9%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 26 has 2 (5.7%) missing valuesMissing
Unnamed: 27 has 2 (5.7%) missing valuesMissing
Unnamed: 28 has 2 (5.7%) missing valuesMissing
Unnamed: 29 has 2 (5.7%) missing valuesMissing
Unnamed: 30 has 2 (5.7%) missing valuesMissing
Unnamed: 31 has 2 (5.7%) missing valuesMissing
Unnamed: 32 has 2 (5.7%) missing valuesMissing
Unnamed: 33 has 2 (5.7%) missing valuesMissing
Unnamed: 34 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 09:49:54.573804
Analysis finished2024-02-10 09:49:56.379318
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:49:56.676540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.875
Min length5

Characters and Unicode

Total characters126
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row행정기관 :
2nd row작성기준 :
3rd row시, 군, 구(읍면동)
4th row전월말세대수
5th row전월말인구수
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
금월말거주불명자수 1
 
3.8%
금월말인구수 1
 
3.8%
금월말세대수 1
 
3.8%
거주불명자수증감 1
 
3.8%
인구수증감 1
 
3.8%
세대수증감 1
 
3.8%
1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T09:49:57.697048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
11
 
8.7%
8
 
6.3%
8
 
6.3%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
4
 
3.2%
Other values (33) 61
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
82.5%
Control 12
 
9.5%
Space Separator 4
 
3.2%
Other Punctuation 4
 
3.2%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
: 2
50.0%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
82.5%
Common 22
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Common
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
82.5%
ASCII 22
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T09:49:58.128430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3636364
Min length2

Characters and Unicode

Total characters26
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)63.6%

Sample

1st row전 입
2nd row복귀
3rd row출생
4th row등록
5th row국외
ValueCountFrequency (%)
국외 2
15.4%
기타 2
15.4%
2
15.4%
1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:49:58.967965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (7) 7
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Control 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T09:49:59.383195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 북구
2nd row2023.03 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2023.03 1
7.1%
현재 1
7.1%
2024-02-10T09:50:00.182365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2
 
4.9%
0 2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 13
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
3 2
33.3%
2 2
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
75.6%
ASCII 10
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:50:00.676596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T09:50:01.384401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:01.935305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4
Min length1

Characters and Unicode

Total characters132
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row198,320
3rd row424,013
4th row1,042
5th row231
ValueCountFrequency (%)
0 4
 
11.8%
1,544 2
 
5.9%
4,649 1
 
2.9%
1,024 1
 
2.9%
423,723 1
 
2.9%
198,569 1
 
2.9%
18 1
 
2.9%
290 1
 
2.9%
249 1
 
2.9%
8 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:50:03.016225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 23
17.4%
1 18
13.6%
, 18
13.6%
4 17
12.9%
0 13
9.8%
8 10
7.6%
9 9
 
6.8%
3 7
 
5.3%
5 5
 
3.8%
7 3
 
2.3%
Other values (5) 9
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
81.8%
Other Punctuation 18
 
13.6%
Space Separator 2
 
1.5%
Dash Punctuation 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 23
21.3%
1 18
16.7%
4 17
15.7%
0 13
12.0%
8 10
9.3%
9 9
 
8.3%
3 7
 
6.5%
5 5
 
4.6%
7 3
 
2.8%
6 3
 
2.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 23
17.7%
1 18
13.8%
, 18
13.8%
4 17
13.1%
0 13
10.0%
8 10
7.7%
9 9
 
6.9%
3 7
 
5.4%
5 5
 
3.8%
7 3
 
2.3%
Other values (3) 7
 
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 23
17.7%
1 18
13.8%
, 18
13.8%
4 17
13.1%
0 13
10.0%
8 10
7.7%
9 9
 
6.9%
3 7
 
5.4%
5 5
 
3.8%
7 3
 
2.3%
Other values (3) 7
 
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:03.358916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row중흥1동
2nd row2,868
3rd row4,524
4th row45
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
5 2
 
6.1%
3 2
 
6.1%
40 1
 
3.0%
4,503 1
 
3.0%
2,863 1
 
3.0%
21 1
 
3.0%
20 1
 
3.0%
37 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:04.214512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
5 9
12.9%
2 9
12.9%
4 8
11.4%
1 7
10.0%
3 7
10.0%
, 4
 
5.7%
8 4
 
5.7%
7 3
 
4.3%
6 3
 
4.3%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
5 9
15.0%
2 9
15.0%
4 8
13.3%
1 7
11.7%
3 7
11.7%
8 4
 
6.7%
7 3
 
5.0%
6 3
 
5.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
5 9
13.4%
2 9
13.4%
4 8
11.9%
1 7
10.4%
3 7
10.4%
, 4
 
6.0%
8 4
 
6.0%
7 3
 
4.5%
6 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.9%
5 9
13.4%
2 9
13.4%
4 8
11.9%
1 7
10.4%
3 7
10.4%
, 4
 
6.0%
8 4
 
6.0%
7 3
 
4.5%
6 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:04.729159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row중흥2동
2nd row4,404
3rd row8,399
4th row36
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
3 2
 
6.1%
60 1
 
3.0%
113 1
 
3.0%
34 1
 
3.0%
8,407 1
 
3.0%
4,419 1
 
3.0%
2 1
 
3.0%
8 1
 
3.0%
15 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:50:05.618851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.7%
3 11
15.7%
4 11
15.7%
1 7
10.0%
6 5
7.1%
, 4
 
5.7%
8 4
 
5.7%
9 4
 
5.7%
2 4
 
5.7%
5 4
 
5.7%
Other values (5) 5
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
88.6%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
3 11
17.7%
4 11
17.7%
1 7
11.3%
6 5
8.1%
8 4
 
6.5%
9 4
 
6.5%
2 4
 
6.5%
5 4
 
6.5%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
4 11
16.4%
1 7
10.4%
6 5
7.5%
, 4
 
6.0%
8 4
 
6.0%
9 4
 
6.0%
2 4
 
6.0%
5 4
 
6.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
4 11
16.4%
1 7
10.4%
6 5
7.5%
, 4
 
6.0%
8 4
 
6.0%
9 4
 
6.0%
2 4
 
6.0%
5 4
 
6.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:06.162502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row중흥3동
2nd row3,664
3rd row6,552
4th row42
5th row2
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
2 2
 
6.1%
52 2
 
6.1%
42 2
 
6.1%
28 1
 
3.0%
85 1
 
3.0%
6,532 1
 
3.0%
3,661 1
 
3.0%
20 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:50:07.234246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
19.4%
3 9
12.5%
0 8
11.1%
6 8
11.1%
4 7
9.7%
5 6
8.3%
1 4
 
5.6%
, 4
 
5.6%
- 3
 
4.2%
7 3
 
4.2%
Other values (5) 6
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
86.1%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
22.6%
3 9
14.5%
0 8
12.9%
6 8
12.9%
4 7
11.3%
5 6
9.7%
1 4
 
6.5%
7 3
 
4.8%
8 2
 
3.2%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
20.3%
3 9
13.0%
0 8
11.6%
6 8
11.6%
4 7
10.1%
5 6
8.7%
1 4
 
5.8%
, 4
 
5.8%
- 3
 
4.3%
7 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
20.3%
3 9
13.0%
0 8
11.6%
6 8
11.6%
4 7
10.1%
5 6
8.7%
1 4
 
5.8%
, 4
 
5.8%
- 3
 
4.3%
7 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:07.684409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row중앙동
2nd row2,285
3rd row3,941
4th row40
5th row6
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
5 2
 
6.1%
6 2
 
6.1%
18 1
 
3.0%
26 1
 
3.0%
3,956 1
 
3.0%
2,280 1
 
3.0%
1 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:08.661762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
1 8
11.9%
5 7
10.4%
2 7
10.4%
3 6
9.0%
6 5
7.5%
9 5
7.5%
4 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
Other values (5) 7
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.0%
1 8
13.8%
5 7
12.1%
2 7
12.1%
3 6
10.3%
6 5
8.6%
9 5
8.6%
4 4
 
6.9%
8 3
 
5.2%
7 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
1 8
12.5%
5 7
10.9%
2 7
10.9%
3 6
9.4%
6 5
7.8%
9 5
7.8%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.2%
1 8
12.5%
5 7
10.9%
2 7
10.9%
3 6
9.4%
6 5
7.8%
9 5
7.8%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:50:09.119447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length2.1764706
Min length1

Characters and Unicode

Total characters74
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)61.8%

Sample

1st row출력일자 :
2nd row임동
3rd row4,603
4th row9,149
5th row30
ValueCountFrequency (%)
0 7
20.0%
25 2
 
5.7%
30 2
 
5.7%
1 2
 
5.7%
5 2
 
5.7%
2 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
42 1
 
2.9%
9,136 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T09:50:09.982162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.5%
1 9
12.2%
3 9
12.2%
5 7
9.5%
9 6
8.1%
6 5
6.8%
2 5
6.8%
4 4
 
5.4%
, 4
 
5.4%
- 3
 
4.1%
Other values (10) 12
16.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
79.7%
Other Letter 6
 
8.1%
Other Punctuation 5
 
6.8%
Dash Punctuation 3
 
4.1%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.9%
1 9
15.3%
3 9
15.3%
5 7
11.9%
9 6
10.2%
6 5
8.5%
2 5
8.5%
4 4
 
6.8%
8 2
 
3.4%
7 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
91.9%
Hangul 6
 
8.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
1 9
13.2%
3 9
13.2%
5 7
10.3%
9 6
8.8%
6 5
7.4%
2 5
7.4%
4 4
 
5.9%
, 4
 
5.9%
- 3
 
4.4%
Other values (4) 6
8.8%
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 68
91.9%
Hangul 6
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
1 9
13.2%
3 9
13.2%
5 7
10.3%
9 6
8.8%
6 5
7.4%
2 5
7.4%
4 4
 
5.9%
, 4
 
5.9%
- 3
 
4.4%
Other values (4) 6
8.8%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:10.354692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row신안동
2nd row7,477
3rd row12,487
4th row75
5th row1
ValueCountFrequency (%)
0 5
 
15.2%
1 4
 
12.1%
60 2
 
6.1%
97 2
 
6.1%
50 2
 
6.1%
8 1
 
3.0%
12,503 1
 
3.0%
7,506 1
 
3.0%
16 1
 
3.0%
29 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:50:11.713654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 12
16.4%
0 11
15.1%
1 10
13.7%
6 6
8.2%
5 6
8.2%
4 6
8.2%
8 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
2 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 12
18.5%
0 11
16.9%
1 10
15.4%
6 6
9.2%
5 6
9.2%
4 6
9.2%
8 5
7.7%
9 4
 
6.2%
2 3
 
4.6%
3 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
7 12
17.1%
0 11
15.7%
1 10
14.3%
6 6
8.6%
5 6
8.6%
4 6
8.6%
8 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 12
17.1%
0 11
15.7%
1 10
14.3%
6 6
8.6%
5 6
8.6%
4 6
8.6%
8 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-04-11 00:00:00
Maximum2023-04-11 00:00:00
2024-02-10T09:50:12.224389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:50:12.531869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:12.863456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row용봉동
2nd row17,927
3rd row37,615
4th row81
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
20 2
 
6.1%
246 1
 
3.0%
474 1
 
3.0%
37,619 1
 
3.0%
18,005 1
 
3.0%
3 1
 
3.0%
4 1
 
3.0%
78 1
 
3.0%
24 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:50:13.683354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17
20.0%
0 12
14.1%
1 10
11.8%
4 8
9.4%
7 6
 
7.1%
9 6
 
7.1%
3 6
 
7.1%
8 6
 
7.1%
, 4
 
4.7%
6 4
 
4.7%
Other values (4) 6
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
91.8%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17
21.8%
0 12
15.4%
1 10
12.8%
4 8
10.3%
7 6
 
7.7%
9 6
 
7.7%
3 6
 
7.7%
8 6
 
7.7%
6 4
 
5.1%
5 3
 
3.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17
20.7%
0 12
14.6%
1 10
12.2%
4 8
9.8%
7 6
 
7.3%
9 6
 
7.3%
3 6
 
7.3%
8 6
 
7.3%
, 4
 
4.9%
6 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17
20.7%
0 12
14.6%
1 10
12.2%
4 8
9.8%
7 6
 
7.3%
9 6
 
7.3%
3 6
 
7.3%
8 6
 
7.3%
, 4
 
4.9%
6 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:14.139646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row운암1동
2nd row7,405
3rd row18,806
4th row22
5th row21
ValueCountFrequency (%)
0 6
 
18.2%
21 2
 
6.1%
101 1
 
3.0%
205 1
 
3.0%
18,769 1
 
3.0%
7,398 1
 
3.0%
2 1
 
3.0%
37 1
 
3.0%
7 1
 
3.0%
6 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:50:14.908731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.4%
1 11
14.1%
2 8
10.3%
8 8
10.3%
7 6
7.7%
6 6
7.7%
4 5
6.4%
5 5
6.4%
, 4
 
5.1%
3 4
 
5.1%
Other values (5) 9
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
17.6%
1 11
16.2%
2 8
11.8%
8 8
11.8%
7 6
8.8%
6 6
8.8%
4 5
7.4%
5 5
7.4%
3 4
 
5.9%
9 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
2 8
10.7%
8 8
10.7%
7 6
8.0%
6 6
8.0%
4 5
6.7%
5 5
6.7%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
2 8
10.7%
8 8
10.7%
7 6
8.0%
6 6
8.0%
4 5
6.7%
5 5
6.7%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:15.177713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row운암2동
2nd row5,984
3rd row11,435
4th row52
5th row9
ValueCountFrequency (%)
0 9
27.3%
52 3
 
9.1%
9 2
 
6.1%
20 1
 
3.0%
11,435 1
 
3.0%
66 1
 
3.0%
5,989 1
 
3.0%
26 1
 
3.0%
5 1
 
3.0%
8 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:50:15.940511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.1%
5 9
12.5%
2 8
11.1%
4 7
9.7%
1 7
9.7%
9 6
8.3%
6 5
 
6.9%
, 4
 
5.6%
7 3
 
4.2%
3 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.3%
5 9
14.1%
2 8
12.5%
4 7
10.9%
1 7
10.9%
9 6
9.4%
6 5
 
7.8%
7 3
 
4.7%
3 3
 
4.7%
8 3
 
4.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.8%
5 9
13.0%
2 8
11.6%
4 7
10.1%
1 7
10.1%
9 6
8.7%
6 5
 
7.2%
, 4
 
5.8%
7 3
 
4.3%
3 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.8%
5 9
13.0%
2 8
11.6%
4 7
10.1%
1 7
10.1%
9 6
8.7%
6 5
 
7.2%
, 4
 
5.8%
7 3
 
4.3%
3 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:16.280462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row운암3동
2nd row5,456
3rd row13,344
4th row35
5th row16
ValueCountFrequency (%)
0 7
21.2%
33 2
 
6.1%
57 2
 
6.1%
4 1
 
3.0%
109 1
 
3.0%
13,368 1
 
3.0%
5,483 1
 
3.0%
2 1
 
3.0%
24 1
 
3.0%
27 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:50:17.093454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.0%
0 10
13.3%
5 9
12.0%
4 8
10.7%
1 8
10.7%
7 5
6.7%
2 5
6.7%
, 4
 
5.3%
6 4
 
5.3%
8 4
 
5.3%
Other values (5) 6
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
17.9%
0 10
14.9%
5 9
13.4%
4 8
11.9%
1 8
11.9%
7 5
7.5%
2 5
7.5%
6 4
 
6.0%
8 4
 
6.0%
9 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
16.7%
0 10
13.9%
5 9
12.5%
4 8
11.1%
1 8
11.1%
7 5
6.9%
2 5
6.9%
, 4
 
5.6%
6 4
 
5.6%
8 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
16.7%
0 10
13.9%
5 9
12.5%
4 8
11.1%
1 8
11.1%
7 5
6.9%
2 5
6.9%
, 4
 
5.6%
6 4
 
5.6%
8 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:17.439857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row동림동
2nd row9,894
3rd row22,769
4th row34
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
6 2
 
6.1%
1 2
 
6.1%
219 1
 
3.0%
22,742 1
 
3.0%
9,900 1
 
3.0%
27 1
 
3.0%
102 1
 
3.0%
78 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:50:18.270907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
9 10
13.3%
2 10
13.3%
1 9
12.0%
7 6
8.0%
6 5
6.7%
8 5
6.7%
3 5
6.7%
, 4
 
5.3%
4 4
 
5.3%
Other values (4) 6
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.4%
9 10
14.9%
2 10
14.9%
1 9
13.4%
7 6
9.0%
6 5
7.5%
8 5
7.5%
3 5
7.5%
4 4
 
6.0%
5 2
 
3.0%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
9 10
13.9%
2 10
13.9%
1 9
12.5%
7 6
8.3%
6 5
6.9%
8 5
6.9%
3 5
6.9%
, 4
 
5.6%
4 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.3%
9 10
13.9%
2 10
13.9%
1 9
12.5%
7 6
8.3%
6 5
6.9%
8 5
6.9%
3 5
6.9%
, 4
 
5.6%
4 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:18.722098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row우산동
2nd row7,503
3rd row15,087
4th row55
5th row8
ValueCountFrequency (%)
0 7
21.2%
57 2
 
6.1%
8 2
 
6.1%
9 1
 
3.0%
76 1
 
3.0%
15,207 1
 
3.0%
7,541 1
 
3.0%
2 1
 
3.0%
120 1
 
3.0%
38 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:50:19.570410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.3%
7 11
14.3%
5 10
13.0%
3 10
13.0%
1 9
11.7%
8 5
6.5%
2 5
6.5%
9 4
 
5.2%
, 4
 
5.2%
4 2
 
2.6%
Other values (5) 6
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
89.6%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.9%
7 11
15.9%
5 10
14.5%
3 10
14.5%
1 9
13.0%
8 5
7.2%
2 5
7.2%
9 4
 
5.8%
4 2
 
2.9%
6 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.9%
7 11
14.9%
5 10
13.5%
3 10
13.5%
1 9
12.2%
8 5
6.8%
2 5
6.8%
9 4
 
5.4%
, 4
 
5.4%
4 2
 
2.7%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
14.9%
7 11
14.9%
5 10
13.5%
3 10
13.5%
1 9
12.2%
8 5
6.8%
2 5
6.8%
9 4
 
5.4%
, 4
 
5.4%
4 2
 
2.7%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:19.897725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row풍향동
2nd row2,683
3rd row5,405
4th row21
5th row2
ValueCountFrequency (%)
0 9
27.3%
2 3
 
9.1%
21 2
 
6.1%
50 2
 
6.1%
34 1
 
3.0%
89 1
 
3.0%
2,686 1
 
3.0%
6 1
 
3.0%
3 1
 
3.0%
27 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:50:20.741802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.5%
2 10
15.4%
3 7
10.8%
1 5
7.7%
5 5
7.7%
4 5
7.7%
, 4
 
6.2%
6 4
 
6.2%
8 4
 
6.2%
9 3
 
4.6%
Other values (4) 6
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.7%
2 10
17.2%
3 7
12.1%
1 5
8.6%
5 5
8.6%
4 5
8.6%
6 4
 
6.9%
8 4
 
6.9%
9 3
 
5.2%
7 3
 
5.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.4%
2 10
16.1%
3 7
11.3%
1 5
8.1%
5 5
8.1%
4 5
8.1%
, 4
 
6.5%
6 4
 
6.5%
8 4
 
6.5%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
19.4%
2 10
16.1%
3 7
11.3%
1 5
8.1%
5 5
8.1%
4 5
8.1%
, 4
 
6.5%
6 4
 
6.5%
8 4
 
6.5%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:21.214346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row문화동
2nd row9,604
3rd row20,131
4th row33
5th row8
ValueCountFrequency (%)
0 7
21.2%
41 2
 
6.1%
8 2
 
6.1%
10 1
 
3.0%
111 1
 
3.0%
20,090 1
 
3.0%
9,593 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
18 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:50:21.995930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.8%
0 14
17.9%
9 7
9.0%
2 6
 
7.7%
3 6
 
7.7%
8 5
 
6.4%
4 5
 
6.4%
5 5
 
6.4%
, 4
 
5.1%
6 2
 
2.6%
Other values (5) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
88.5%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
24.6%
0 14
20.3%
9 7
10.1%
2 6
 
8.7%
3 6
 
8.7%
8 5
 
7.2%
4 5
 
7.2%
5 5
 
7.2%
6 2
 
2.9%
7 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
22.7%
0 14
18.7%
9 7
9.3%
2 6
 
8.0%
3 6
 
8.0%
8 5
 
6.7%
4 5
 
6.7%
5 5
 
6.7%
, 4
 
5.3%
6 2
 
2.7%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
22.7%
0 14
18.7%
9 7
9.3%
2 6
 
8.0%
3 6
 
8.0%
8 5
 
6.7%
4 5
 
6.7%
5 5
 
6.7%
, 4
 
5.3%
6 2
 
2.7%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:22.405994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row문흥1동
2nd row6,396
3rd row15,290
4th row20
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
20 2
 
6.1%
48 1
 
3.0%
15,290 1
 
3.0%
62 1
 
3.0%
15,469 1
 
3.0%
6,568 1
 
3.0%
1 1
 
3.0%
179 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:23.188056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.7%
0 12
15.2%
6 10
12.7%
9 9
11.4%
2 6
7.6%
3 5
 
6.3%
5 5
 
6.3%
7 4
 
5.1%
4 4
 
5.1%
, 4
 
5.1%
Other values (5) 6
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
89.9%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
19.7%
0 12
16.9%
6 10
14.1%
9 9
12.7%
2 6
8.5%
3 5
 
7.0%
5 5
 
7.0%
7 4
 
5.6%
4 4
 
5.6%
8 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.4%
0 12
15.8%
6 10
13.2%
9 9
11.8%
2 6
7.9%
3 5
 
6.6%
5 5
 
6.6%
7 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.4%
0 12
15.8%
6 10
13.2%
9 9
11.8%
2 6
7.9%
3 5
 
6.6%
5 5
 
6.6%
7 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:23.631421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row문흥2동
2nd row7,375
3rd row15,177
4th row21
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
21 2
 
6.1%
72 2
 
6.1%
43 1
 
3.0%
15,177 1
 
3.0%
141 1
 
3.0%
7,379 1
 
3.0%
4 1
 
3.0%
13 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:50:24.338397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.3%
7 10
13.9%
5 9
12.5%
0 8
11.1%
2 8
11.1%
4 8
11.1%
3 5
6.9%
, 4
 
5.6%
6 2
 
2.8%
9 2
 
2.8%
Other values (5) 5
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
17.2%
7 10
15.6%
5 9
14.1%
0 8
12.5%
2 8
12.5%
4 8
12.5%
3 5
7.8%
6 2
 
3.1%
9 2
 
3.1%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.9%
7 10
14.5%
5 9
13.0%
0 8
11.6%
2 8
11.6%
4 8
11.6%
3 5
7.2%
, 4
 
5.8%
6 2
 
2.9%
9 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.9%
7 10
14.5%
5 9
13.0%
0 8
11.6%
2 8
11.6%
4 8
11.6%
3 5
7.2%
, 4
 
5.8%
6 2
 
2.9%
9 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:24.683486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row두암1동
2nd row3,947
3rd row7,405
4th row12
5th row9
ValueCountFrequency (%)
0 7
21.2%
29 2
 
6.1%
12 2
 
6.1%
9 2
 
6.1%
4 2
 
6.1%
1 2
 
6.1%
14 1
 
3.0%
32 1
 
3.0%
3,952 1
 
3.0%
5 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:50:25.631062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
14.9%
0 9
13.4%
1 9
13.4%
9 7
10.4%
4 7
10.4%
7 6
9.0%
5 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
6 3
 
4.5%
Other values (4) 4
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
16.9%
0 9
15.3%
1 9
15.3%
9 7
11.9%
4 7
11.9%
7 6
10.2%
5 4
 
6.8%
3 4
 
6.8%
6 3
 
5.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
15.6%
0 9
14.1%
1 9
14.1%
9 7
10.9%
4 7
10.9%
7 6
9.4%
5 4
 
6.2%
, 4
 
6.2%
3 4
 
6.2%
6 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
15.6%
0 9
14.1%
1 9
14.1%
9 7
10.9%
4 7
10.9%
7 6
9.4%
5 4
 
6.2%
, 4
 
6.2%
3 4
 
6.2%
6 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:26.024592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row두암2동
2nd row7,608
3rd row15,430
4th row48
5th row9
ValueCountFrequency (%)
0 7
21.2%
82 2
 
6.1%
57 2
 
6.1%
4 2
 
6.1%
9 2
 
6.1%
35 1
 
3.0%
155 1
 
3.0%
74 1
 
3.0%
15,414 1
 
3.0%
7,612 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:50:26.988564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.8%
4 10
13.7%
0 9
12.3%
5 8
11.0%
8 6
8.2%
7 6
8.2%
2 4
 
5.5%
, 4
 
5.5%
6 4
 
5.5%
9 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.0%
4 10
15.4%
0 9
13.8%
5 8
12.3%
8 6
9.2%
7 6
9.2%
2 4
 
6.2%
6 4
 
6.2%
9 3
 
4.6%
3 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.6%
4 10
14.3%
0 9
12.9%
5 8
11.4%
8 6
8.6%
7 6
8.6%
2 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
18.6%
4 10
14.3%
0 9
12.9%
5 8
11.4%
8 6
8.6%
7 6
8.6%
2 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:27.450125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row두암3동
2nd row7,653
3rd row12,778
4th row38
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
46 2
 
6.1%
1 2
 
6.1%
36 2
 
6.1%
24 2
 
6.1%
8 2
 
6.1%
2 2
 
6.1%
41 1
 
3.0%
72 1
 
3.0%
7,629 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:50:28.506405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
14.7%
3 8
10.7%
6 7
9.3%
1 7
9.3%
7 7
9.3%
0 6
8.0%
4 6
8.0%
5 5
6.7%
8 4
 
5.3%
, 4
 
5.3%
Other values (5) 10
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
16.9%
3 8
12.3%
6 7
10.8%
1 7
10.8%
7 7
10.8%
0 6
9.2%
4 6
9.2%
5 5
7.7%
8 4
 
6.2%
9 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
15.3%
3 8
11.1%
6 7
9.7%
1 7
9.7%
7 7
9.7%
0 6
8.3%
4 6
8.3%
5 5
6.9%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 7
9.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
15.3%
3 8
11.1%
6 7
9.7%
1 7
9.7%
7 7
9.7%
0 6
8.3%
4 6
8.3%
5 5
6.9%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 7
9.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:28.941986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row삼각동
2nd row5,994
3rd row13,590
4th row29
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
3 2
 
6.1%
4 2
 
6.1%
94 1
 
3.0%
163 1
 
3.0%
13,537 1
 
3.0%
5,991 1
 
3.0%
2 1
 
3.0%
53 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:50:29.895480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.2%
1 9
12.2%
9 9
12.2%
4 8
10.8%
3 7
9.5%
5 6
8.1%
2 6
8.1%
6 5
6.8%
, 4
5.4%
7 4
5.4%
Other values (5) 7
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
14.1%
1 9
14.1%
9 9
14.1%
4 8
12.5%
3 7
10.9%
5 6
9.4%
2 6
9.4%
6 5
7.8%
7 4
6.2%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
12.7%
1 9
12.7%
9 9
12.7%
4 8
11.3%
3 7
9.9%
5 6
8.5%
2 6
8.5%
6 5
7.0%
, 4
5.6%
7 4
5.6%
Other values (2) 4
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
12.7%
1 9
12.7%
9 9
12.7%
4 8
11.3%
3 7
9.9%
5 6
8.5%
2 6
8.5%
6 5
7.0%
, 4
5.6%
7 4
5.6%
Other values (2) 4
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:30.226166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row일곡동
2nd row11,470
3rd row28,744
4th row24
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
76 2
 
6.1%
24 2
 
6.1%
10 1
 
3.0%
137 1
 
3.0%
11,464 1
 
3.0%
98 1
 
3.0%
6 1
 
3.0%
14 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:31.031253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
14.8%
1 12
14.8%
2 11
13.6%
0 9
11.1%
6 9
11.1%
7 7
8.6%
8 5
6.2%
, 4
 
4.9%
5 3
 
3.7%
9 2
 
2.5%
Other values (5) 7
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
88.9%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
16.7%
1 12
16.7%
2 11
15.3%
0 9
12.5%
6 9
12.5%
7 7
9.7%
8 5
6.9%
5 3
 
4.2%
9 2
 
2.8%
3 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
15.4%
1 12
15.4%
2 11
14.1%
0 9
11.5%
6 9
11.5%
7 7
9.0%
8 5
6.4%
, 4
 
5.1%
5 3
 
3.8%
9 2
 
2.6%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
15.4%
1 12
15.4%
2 11
14.1%
0 9
11.5%
6 9
11.5%
7 7
9.0%
8 5
6.4%
, 4
 
5.1%
5 3
 
3.8%
9 2
 
2.6%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:31.532899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row매곡동
2nd row5,498
3rd row13,530
4th row15
5th row4
ValueCountFrequency (%)
0 5
 
15.2%
4 3
 
9.1%
59 2
 
6.1%
37 2
 
6.1%
1 2
 
6.1%
34 1
 
3.0%
120 1
 
3.0%
13,507 1
 
3.0%
5,516 1
 
3.0%
23 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:32.504144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.9%
0 9
12.5%
4 9
12.5%
3 9
12.5%
5 8
11.1%
9 6
8.3%
, 4
 
5.6%
2 4
 
5.6%
7 3
 
4.2%
8 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
15.9%
0 9
14.3%
4 9
14.3%
3 9
14.3%
5 8
12.7%
9 6
9.5%
2 4
 
6.3%
7 3
 
4.8%
8 3
 
4.8%
6 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
14.5%
0 9
13.0%
4 9
13.0%
3 9
13.0%
5 8
11.6%
9 6
8.7%
, 4
 
5.8%
2 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
14.5%
0 9
13.0%
4 9
13.0%
3 9
13.0%
5 8
11.6%
9 6
8.7%
, 4
 
5.8%
2 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:32.837405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row오치1동
2nd row5,388
3rd row10,400
4th row55
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
73 1
 
3.0%
156 1
 
3.0%
10,344 1
 
3.0%
5,377 1
 
3.0%
3 1
 
3.0%
56 1
 
3.0%
11 1
 
3.0%
9 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:50:33.774326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.9%
1 13
16.9%
5 8
10.4%
3 8
10.4%
4 6
7.8%
6 6
7.8%
, 4
 
5.2%
7 4
 
5.2%
8 3
 
3.9%
2 3
 
3.9%
Other values (5) 9
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.4%
1 13
19.4%
5 8
11.9%
3 8
11.9%
4 6
9.0%
6 6
9.0%
7 4
 
6.0%
8 3
 
4.5%
2 3
 
4.5%
9 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.6%
1 13
17.6%
5 8
10.8%
3 8
10.8%
4 6
8.1%
6 6
8.1%
, 4
 
5.4%
7 4
 
5.4%
8 3
 
4.1%
2 3
 
4.1%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.6%
1 13
17.6%
5 8
10.8%
3 8
10.8%
4 6
8.1%
6 6
8.1%
, 4
 
5.4%
7 4
 
5.4%
8 3
 
4.1%
2 3
 
4.1%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:34.105249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row오치2동
2nd row6,866
3rd row11,949
4th row33
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
33 2
 
6.1%
6 2
 
6.1%
64 1
 
3.0%
11,949 1
 
3.0%
158 1
 
3.0%
11,960 1
 
3.0%
6,872 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:50:35.033121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.9%
6 12
16.2%
0 11
14.9%
3 7
9.5%
9 5
 
6.8%
4 5
 
6.8%
5 4
 
5.4%
8 4
 
5.4%
, 4
 
5.4%
2 3
 
4.1%
Other values (4) 5
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
90.5%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.9%
6 12
17.9%
0 11
16.4%
3 7
10.4%
9 5
 
7.5%
4 5
 
7.5%
5 4
 
6.0%
8 4
 
6.0%
2 3
 
4.5%
7 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.7%
6 12
16.9%
0 11
15.5%
3 7
9.9%
9 5
 
7.0%
4 5
 
7.0%
5 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
2 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.7%
6 12
16.9%
0 11
15.5%
3 7
9.9%
9 5
 
7.0%
4 5
 
7.0%
5 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
2 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:35.415571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row석곡동
2nd row1,335
3rd row2,387
4th row9
5th row3
ValueCountFrequency (%)
0 8
24.2%
11 3
 
9.1%
3 3
 
9.1%
1 2
 
6.1%
12 2
 
6.1%
8 2
 
6.1%
13 2
 
6.1%
10 1
 
3.0%
1,324 1
 
3.0%
14 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:50:36.365037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
24.2%
3 12
18.2%
0 9
13.6%
2 8
12.1%
, 4
 
6.1%
8 3
 
4.5%
4 3
 
4.5%
- 3
 
4.5%
5 2
 
3.0%
7 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
84.8%
Other Punctuation 4
 
6.1%
Dash Punctuation 3
 
4.5%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
28.6%
3 12
21.4%
0 9
16.1%
2 8
14.3%
8 3
 
5.4%
4 3
 
5.4%
5 2
 
3.6%
7 2
 
3.6%
9 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
25.4%
3 12
19.0%
0 9
14.3%
2 8
12.7%
, 4
 
6.3%
8 3
 
4.8%
4 3
 
4.8%
- 3
 
4.8%
5 2
 
3.2%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
25.4%
3 12
19.0%
0 9
14.3%
2 8
12.7%
, 4
 
6.3%
8 3
 
4.8%
4 3
 
4.8%
- 3
 
4.8%
5 2
 
3.2%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:36.707941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row건국동
2nd row8,986
3rd row21,726
4th row56
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
9 3
 
9.1%
122 1
 
3.0%
21,684 1
 
3.0%
8,977 1
 
3.0%
2 1
 
3.0%
42 1
 
3.0%
1 1
 
3.0%
98 1
 
3.0%
65 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:50:37.575371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.4%
0 10
12.8%
1 10
12.8%
8 9
11.5%
9 7
9.0%
7 6
7.7%
6 5
6.4%
4 5
6.4%
, 4
 
5.1%
5 3
 
3.8%
Other values (5) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
17.6%
0 10
14.7%
1 10
14.7%
8 9
13.2%
9 7
10.3%
7 6
8.8%
6 5
7.4%
4 5
7.4%
5 3
 
4.4%
3 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.0%
0 10
13.3%
1 10
13.3%
8 9
12.0%
9 7
9.3%
7 6
8.0%
6 5
6.7%
4 5
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
16.0%
0 10
13.3%
1 10
13.3%
8 9
12.0%
9 7
9.3%
7 6
8.0%
6 5
6.7%
4 5
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:38.027888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row양산동
2nd row16,258
3rd row36,815
4th row68
5th row16
ValueCountFrequency (%)
0 6
 
18.2%
76 2
 
6.1%
13 2
 
6.1%
134 2
 
6.1%
99 1
 
3.0%
167 1
 
3.0%
73 1
 
3.0%
36,717 1
 
3.0%
16,233 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:50:39.003135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.6%
6 12
14.0%
3 10
11.6%
2 8
9.3%
0 7
8.1%
7 7
8.1%
8 7
8.1%
, 4
 
4.7%
5 4
 
4.7%
4 3
 
3.5%
Other values (5) 8
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.8%
6 12
15.6%
3 10
13.0%
2 8
10.4%
0 7
9.1%
7 7
9.1%
8 7
9.1%
5 4
 
5.2%
4 3
 
3.9%
9 3
 
3.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.3%
6 12
14.5%
3 10
12.0%
2 8
9.6%
0 7
8.4%
7 7
8.4%
8 7
8.4%
, 4
 
4.8%
5 4
 
4.8%
4 3
 
3.6%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.3%
6 12
14.5%
3 10
12.0%
2 8
9.6%
0 7
8.4%
7 7
8.4%
8 7
8.4%
, 4
 
4.8%
5 4
 
4.8%
4 3
 
3.6%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:39.492833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row신용동
2nd row11,789
3rd row29,148
4th row13
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
1 2
 
6.1%
161 1
 
3.0%
29,117 1
 
3.0%
11,756 1
 
3.0%
31 1
 
3.0%
33 1
 
3.0%
4 1
 
3.0%
112 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:50:40.435084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
28.2%
0 10
11.8%
2 10
11.8%
7 8
 
9.4%
3 6
 
7.1%
9 5
 
5.9%
4 5
 
5.9%
, 4
 
4.7%
8 3
 
3.5%
- 3
 
3.5%
Other values (5) 7
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
88.2%
Other Punctuation 4
 
4.7%
Dash Punctuation 3
 
3.5%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
32.0%
0 10
13.3%
2 10
13.3%
7 8
 
10.7%
3 6
 
8.0%
9 5
 
6.7%
4 5
 
6.7%
8 3
 
4.0%
5 2
 
2.7%
6 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
29.3%
0 10
12.2%
2 10
12.2%
7 8
 
9.8%
3 6
 
7.3%
9 5
 
6.1%
4 5
 
6.1%
, 4
 
4.9%
8 3
 
3.7%
- 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
29.3%
0 10
12.2%
2 10
12.2%
7 8
 
9.8%
3 6
 
7.3%
9 5
 
6.1%
4 5
 
6.1%
, 4
 
4.9%
8 3
 
3.7%
- 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 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: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.04.11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.03 현재<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>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계중흥1동중흥2동중흥3동중앙동임동신안동<NA>용봉동운암1동운암2동운암3동동림동우산동풍향동문화동문흥1동문흥2동두암1동두암2동두암3동삼각동일곡동매곡동오치1동오치2동석곡동건국동양산동신용동
3<NA>전월말세대수<NA><NA><NA>198,3202,8684,4043,6642,2854,6037,477<NA>17,9277,4055,9845,4569,8947,5032,6839,6046,3967,3753,9477,6087,6535,99411,4705,4985,3886,8661,3358,98616,25811,789
4<NA>전월말인구수<NA><NA><NA>424,0134,5248,3996,5523,9419,14912,487<NA>37,61518,80611,43513,34422,76915,0875,40520,13115,29015,1777,40515,43012,77813,59028,74413,53010,40011,9492,38721,72636,81529,148
5<NA>전월말거주불명자수<NA><NA><NA>1,042453642403075<NA>8122523534552133202112483829241555339566813
6<NA>전월말재외국민등록자수<NA><NA><NA>231162651<NA>2021916782895998412410103101610
7<NA>증 가 요 인전 입<NA>4,407561201165767186<NA>4921641221381822739719131714167155921161689910615823189268247
8<NA><NA><NA>남자<NA>2,288326472273797<NA>26383527093137478916669427446709240619212107134120
9<NA><NA><NA>여자<NA>2,119245644303089<NA>22981706889136501021517225814646765945661182134127
Unnamed: 0인구이동보고서(1호)Unnamed: 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: 34
25<NA><NA>말소<NA><NA>8000003<NA>0000000000001002000101
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>249-515-3-5-829<NA>78-75276383-11172454-24-3-618-116-11-9-25-33
29<NA>인구수증감<NA><NA><NA>-290-218-2015-1316<NA>4-37-2624-271206-41179-5-4-16-49-53-98-23-5611-13-42-98-31
30<NA>거주불명자수증감<NA><NA><NA>-18-3-2-3-1-1-1<NA>3-20-21-201-1001-2-20-1-31-1-25-1
31<NA>금월말세대수<NA><NA><NA>198,5692,8634,4193,6612,2804,5957,506<NA>18,0057,3985,9895,4839,9007,5412,6869,5936,5687,3793,9527,6127,6295,99111,4645,5165,3776,8721,3248,97716,23311,756
32<NA>금월말인구수<NA><NA><NA>423,7234,5038,4076,5323,9569,13612,503<NA>37,61918,76911,40913,36822,74215,2075,41120,09015,46915,1727,40115,41412,72913,53728,64613,50710,34411,9602,37421,68436,71729,117
33<NA>금월말거주불명자수<NA><NA><NA>1,024423439392974<NA>8420523335532134192112493627241452348547312
34<NA>금월말재외국민등록자수<NA><NA><NA>232152651<NA>202191778289599841241010391810

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 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: 34# duplicates
0<NA>기타<NA><NA>0000000<NA>00000000000000000000002