Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text23
DateTime1

Dataset

Description2023-05-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

Alerts

Unnamed: 12 has constant value ""Constant
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: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 07:21:36.957391
Analysis finished2024-02-10 07:21:38.319897
Duration1.36 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
2024-02-10T07:21:38.628350image/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%
2024-02-10T07:21:39.658672image/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
2024-02-10T07:21:40.091660image/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%
2024-02-10T07:21:41.097663image/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
2024-02-10T07:21:41.569011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters21
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 서구
2nd row2023.04 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%
서구 1
7.1%
2023.04 1
7.1%
현재 1
7.1%
2024-02-10T07:21:42.259282image/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%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (11) 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 (%)
2 2
33.3%
0 2
33.3%
3 1
16.7%
4 1
16.7%
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%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 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%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:21:42.698212image/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%
2024-02-10T07:21:43.632629image/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
2024-02-10T07:21:44.114491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.4545455
Min length1

Characters and Unicode

Total characters114
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 row133,935
3rd row286,826
4th row837
5th row154
ValueCountFrequency (%)
0 4
 
11.8%
11 2
 
5.9%
806 2
 
5.9%
1,361 1
 
2.9%
2,705 1
 
2.9%
826 1
 
2.9%
286,574 1
 
2.9%
134,000 1
 
2.9%
252 1
 
2.9%
65 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T07:21:45.061706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
14.0%
2 14
12.3%
8 12
10.5%
0 11
9.6%
, 10
8.8%
5 10
8.8%
6 9
7.9%
3 8
7.0%
4 7
6.1%
7 6
 
5.3%
Other values (5) 11
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
86.0%
Other Punctuation 10
 
8.8%
Space Separator 2
 
1.8%
Dash Punctuation 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
16.3%
2 14
14.3%
8 12
12.2%
0 11
11.2%
5 10
10.2%
6 9
9.2%
3 8
8.2%
4 7
7.1%
7 6
 
6.1%
9 5
 
5.1%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112
98.2%
Hangul 2
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
14.3%
2 14
12.5%
8 12
10.7%
0 11
9.8%
, 10
8.9%
5 10
8.9%
6 9
8.0%
3 8
7.1%
4 7
6.2%
7 6
 
5.4%
Other values (3) 9
8.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
98.2%
Hangul 2
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
14.3%
2 14
12.5%
8 12
10.7%
0 11
9.8%
, 10
8.9%
5 10
8.9%
6 9
8.0%
3 8
7.1%
4 7
6.2%
7 6
 
5.4%
Other values (3) 9
8.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:45.632141image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row양동
2nd row1,972
3rd row3,396
4th row27
5th row3
ValueCountFrequency (%)
0 9
27.3%
5 3
 
9.1%
3 2
 
6.1%
13 2
 
6.1%
10 2
 
6.1%
11 1
 
3.0%
3,380 1
 
3.0%
1,961 1
 
3.0%
2 1
 
3.0%
16 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:21:46.684381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.7%
1 11
16.7%
3 10
15.2%
2 7
10.6%
5 4
 
6.1%
, 4
 
6.1%
4 3
 
4.5%
9 3
 
4.5%
6 3
 
4.5%
- 3
 
4.5%
Other values (4) 5
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
86.4%
Other Punctuation 4
 
6.1%
Dash Punctuation 3
 
4.5%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
22.8%
1 11
19.3%
3 10
17.5%
2 7
12.3%
5 4
 
7.0%
4 3
 
5.3%
9 3
 
5.3%
6 3
 
5.3%
7 2
 
3.5%
8 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.3%
1 11
17.2%
3 10
15.6%
2 7
10.9%
5 4
 
6.2%
, 4
 
6.2%
4 3
 
4.7%
9 3
 
4.7%
6 3
 
4.7%
- 3
 
4.7%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.3%
1 11
17.2%
3 10
15.6%
2 7
10.9%
5 4
 
6.2%
, 4
 
6.2%
4 3
 
4.7%
9 3
 
4.7%
6 3
 
4.7%
- 3
 
4.7%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:47.002618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters13
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

Unique12 ?
Unique (%)36.4%

Sample

1st row양3동
2nd row2,141
3rd row4,368
4th row30
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 4
12.1%
11 3
9.1%
17 3
9.1%
6 3
9.1%
30 2
 
6.1%
13 2
 
6.1%
양3동 1
 
3.0%
2,141 1
 
3.0%
4,368 1
 
3.0%
Other values (6) 6
18.2%
2024-02-10T07:21:47.984521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
27.7%
0 9
13.8%
3 9
13.8%
4 5
 
7.7%
7 4
 
6.2%
6 4
 
6.2%
, 4
 
6.2%
5 4
 
6.2%
2 3
 
4.6%
- 2
 
3.1%
Other values (3) 3
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
31.6%
0 9
15.8%
3 9
15.8%
4 5
 
8.8%
7 4
 
7.0%
6 4
 
7.0%
5 4
 
7.0%
2 3
 
5.3%
8 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
28.6%
0 9
14.3%
3 9
14.3%
4 5
 
7.9%
7 4
 
6.3%
6 4
 
6.3%
, 4
 
6.3%
5 4
 
6.3%
2 3
 
4.8%
- 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
28.6%
0 9
14.3%
3 9
14.3%
4 5
 
7.9%
7 4
 
6.3%
6 4
 
6.3%
, 4
 
6.3%
5 4
 
6.3%
2 3
 
4.8%
- 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:48.459854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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

Unique24 ?
Unique (%)72.7%

Sample

1st row농성1동
2nd row6,556
3rd row11,411
4th row42
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
73 1
 
3.0%
11,430 1
 
3.0%
6,573 1
 
3.0%
1 1
 
3.0%
19 1
 
3.0%
17 1
 
3.0%
9 1
 
3.0%
36 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:49.245368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.4%
0 10
13.9%
6 8
11.1%
5 8
11.1%
4 7
9.7%
7 6
8.3%
3 5
 
6.9%
, 4
 
5.6%
8 3
 
4.2%
2 2
 
2.8%
Other values (4) 5
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.5%
0 10
15.4%
6 8
12.3%
5 8
12.3%
4 7
10.8%
7 6
9.2%
3 5
 
7.7%
8 3
 
4.6%
2 2
 
3.1%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.3%
0 10
14.5%
6 8
11.6%
5 8
11.6%
4 7
10.1%
7 6
8.7%
3 5
 
7.2%
, 4
 
5.8%
8 3
 
4.3%
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 14
20.3%
0 10
14.5%
6 8
11.6%
5 8
11.6%
4 7
10.1%
7 6
8.7%
3 5
 
7.2%
, 4
 
5.8%
8 3
 
4.3%
2 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:49.626658image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성2동
2nd row2,867
3rd row4,592
4th row45
5th row0
ValueCountFrequency (%)
0 8
24.2%
22 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
12 2
 
6.1%
30 1
 
3.0%
57 1
 
3.0%
27 1
 
3.0%
4,576 1
 
3.0%
2,861 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:21:50.575735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.6%
1 10
14.3%
0 9
12.9%
4 7
10.0%
7 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
5 4
 
5.7%
3 3
 
4.3%
- 3
 
4.3%
Other values (5) 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 (%)
2 13
21.7%
1 10
16.7%
0 9
15.0%
4 7
11.7%
7 6
10.0%
6 5
 
8.3%
5 4
 
6.7%
3 3
 
5.0%
8 2
 
3.3%
9 1
 
1.7%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
19.4%
1 10
14.9%
0 9
13.4%
4 7
10.4%
7 6
9.0%
6 5
 
7.5%
, 4
 
6.0%
5 4
 
6.0%
3 3
 
4.5%
- 3
 
4.5%
Other values (2) 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 (%)
2 13
19.4%
1 10
14.9%
0 9
13.4%
4 7
10.4%
7 6
9.0%
6 5
 
7.5%
, 4
 
6.0%
5 4
 
6.0%
3 3
 
4.5%
- 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct22
Distinct (%)64.7%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:21:51.024905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
Distinct characters21
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

Unique17 ?
Unique (%)50.0%

Sample

1st row출력일자 :
2nd row광천동
3rd row3,997
4th row7,511
5th row63
ValueCountFrequency (%)
0 9
25.7%
40 2
 
5.7%
30 2
 
5.7%
63 2
 
5.7%
15 2
 
5.7%
13 2
 
5.7%
77 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
3,982 1
 
2.9%
Other values (12) 12
34.3%
2024-02-10T07:21:51.962006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.4%
1 11
14.5%
3 9
11.8%
7 8
10.5%
4 5
 
6.6%
5 4
 
5.3%
, 4
 
5.3%
2 3
 
3.9%
9 3
 
3.9%
- 2
 
2.6%
Other values (11) 13
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
80.3%
Other Letter 7
 
9.2%
Other Punctuation 5
 
6.6%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.0%
1 11
18.0%
3 9
14.8%
7 8
13.1%
4 5
 
8.2%
5 4
 
6.6%
2 3
 
4.9%
9 3
 
4.9%
8 2
 
3.3%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
90.8%
Hangul 7
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.3%
1 11
15.9%
3 9
13.0%
7 8
11.6%
4 5
 
7.2%
5 4
 
5.8%
, 4
 
5.8%
2 3
 
4.3%
9 3
 
4.3%
- 2
 
2.9%
Other values (4) 6
8.7%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
90.8%
Hangul 7
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.3%
1 11
15.9%
3 9
13.0%
7 8
11.6%
4 5
 
7.2%
5 4
 
5.8%
, 4
 
5.8%
2 3
 
4.3%
9 3
 
4.3%
- 2
 
2.9%
Other values (4) 6
8.7%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Unnamed: 11
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:52.407166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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 row유덕동
2nd row4,859
3rd row10,606
4th row20
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
62 1
 
3.0%
10,589 1
 
3.0%
4,852 1
 
3.0%
2 1
 
3.0%
17 1
 
3.0%
7 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:53.301739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.7%
1 8
11.3%
2 8
11.3%
3 6
8.5%
8 6
8.5%
4 5
 
7.0%
6 5
 
7.0%
, 4
 
5.6%
7 4
 
5.6%
5 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
87.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
22.6%
1 8
12.9%
2 8
12.9%
3 6
9.7%
8 6
9.7%
4 5
 
8.1%
6 5
 
8.1%
7 4
 
6.5%
5 3
 
4.8%
9 3
 
4.8%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.6%
1 8
11.8%
2 8
11.8%
3 6
8.8%
8 6
8.8%
4 5
 
7.4%
6 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
5 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.6%
1 8
11.8%
2 8
11.8%
3 6
8.8%
8 6
8.8%
4 5
 
7.4%
6 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
5 3
 
4.4%
Other values (2) 5
 
7.4%
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
Minimum2023-05-01 00:00:00
Maximum2023-05-01 00:00:00
2024-02-10T07:21:54.188609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:21:54.578165image/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
2024-02-10T07:21:54.889887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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 row치평동
2nd row13,594
3rd row29,389
4th row57
5th row16
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
125 1
 
3.0%
29,389 1
 
3.0%
131 1
 
3.0%
58 1
 
3.0%
29,392 1
 
3.0%
13,641 1
 
3.0%
3 1
 
3.0%
47 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:21:55.834969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.8%
0 9
11.1%
2 8
9.9%
3 8
9.9%
5 7
8.6%
9 7
8.6%
4 5
 
6.2%
8 5
 
6.2%
7 5
 
6.2%
6 4
 
4.9%
Other values (4) 7
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
91.4%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.6%
0 9
12.2%
2 8
10.8%
3 8
10.8%
5 7
9.5%
9 7
9.5%
4 5
 
6.8%
8 5
 
6.8%
7 5
 
6.8%
6 4
 
5.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.5%
0 9
11.5%
2 8
10.3%
3 8
10.3%
5 7
9.0%
9 7
9.0%
4 5
 
6.4%
8 5
 
6.4%
7 5
 
6.4%
6 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 (%)
1 16
20.5%
0 9
11.5%
2 8
10.3%
3 8
10.3%
5 7
9.0%
9 7
9.0%
4 5
 
6.4%
8 5
 
6.4%
7 5
 
6.4%
6 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:56.369877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
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 row상무1동
2nd row12,243
3rd row24,226
4th row163
5th row10
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
78 2
 
6.1%
290 1
 
3.0%
146 1
 
3.0%
157 1
 
3.0%
24,194 1
 
3.0%
12,258 1
 
3.0%
6 1
 
3.0%
32 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:21:57.316643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.0%
2 13
14.9%
0 11
12.6%
4 7
 
8.0%
9 6
 
6.9%
7 5
 
5.7%
8 4
 
4.6%
, 4
 
4.6%
3 4
 
4.6%
6 4
 
4.6%
Other values (5) 9
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
89.7%
Other Punctuation 4
 
4.6%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
25.6%
2 13
16.7%
0 11
14.1%
4 7
 
9.0%
9 6
 
7.7%
7 5
 
6.4%
8 4
 
5.1%
3 4
 
5.1%
6 4
 
5.1%
5 4
 
5.1%
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 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.8%
2 13
15.5%
0 11
13.1%
4 7
 
8.3%
9 6
 
7.1%
7 5
 
6.0%
8 4
 
4.8%
, 4
 
4.8%
3 4
 
4.8%
6 4
 
4.8%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.8%
2 13
15.5%
0 11
13.1%
4 7
 
8.3%
9 6
 
7.1%
7 5
 
6.0%
8 4
 
4.8%
, 4
 
4.8%
3 4
 
4.8%
6 4
 
4.8%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:57.731111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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 row상무2동
2nd row12,980
3rd row22,951
4th row103
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
103 2
 
6.1%
85 2
 
6.1%
96 1
 
3.0%
22,951 1
 
3.0%
205 1
 
3.0%
12,995 1
 
3.0%
25 1
 
3.0%
15 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:21:58.570432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
18.5%
0 14
17.3%
1 11
13.6%
5 10
12.3%
9 8
9.9%
8 6
 
7.4%
, 4
 
4.9%
3 3
 
3.7%
6 3
 
3.7%
7 2
 
2.5%
Other values (5) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
90.1%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
20.5%
0 14
19.2%
1 11
15.1%
5 10
13.7%
9 8
11.0%
8 6
 
8.2%
3 3
 
4.1%
6 3
 
4.1%
7 2
 
2.7%
4 1
 
1.4%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
19.2%
0 14
17.9%
1 11
14.1%
5 10
12.8%
9 8
10.3%
8 6
 
7.7%
, 4
 
5.1%
3 3
 
3.8%
6 3
 
3.8%
7 2
 
2.6%
Other values (2) 2
 
2.6%
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 (%)
2 15
19.2%
0 14
17.9%
1 11
14.1%
5 10
12.8%
9 8
10.3%
8 6
 
7.7%
, 4
 
5.1%
3 3
 
3.8%
6 3
 
3.8%
7 2
 
2.6%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:58.917450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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 row화정1동
2nd row8,695
3rd row15,664
4th row45
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 3
 
9.1%
45 2
 
6.1%
86 1
 
3.0%
15,664 1
 
3.0%
8,695 1
 
3.0%
8,707 1
 
3.0%
9 1
 
3.0%
12 1
 
3.0%
52 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:21:59.832472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 10
14.1%
0 9
12.7%
5 9
12.7%
8 8
11.3%
1 7
9.9%
4 6
8.5%
7 6
8.5%
9 4
 
5.6%
, 4
 
5.6%
3 3
 
4.2%
Other values (4) 5
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
90.1%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 10
15.6%
0 9
14.1%
5 9
14.1%
8 8
12.5%
1 7
10.9%
4 6
9.4%
7 6
9.4%
9 4
 
6.2%
3 3
 
4.7%
2 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
6 10
14.7%
0 9
13.2%
5 9
13.2%
8 8
11.8%
1 7
10.3%
4 6
8.8%
7 6
8.8%
9 4
 
5.9%
, 4
 
5.9%
3 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 10
14.7%
0 9
13.2%
5 9
13.2%
8 8
11.8%
1 7
10.3%
4 6
8.8%
7 6
8.8%
9 4
 
5.9%
, 4
 
5.9%
3 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:00.164981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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 row화정2동
2nd row7,909
3rd row19,941
4th row30
5th row16
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
77 2
 
6.1%
58 1
 
3.0%
85 1
 
3.0%
29 1
 
3.0%
19,930 1
 
3.0%
7,920 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:22:00.863799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
0 11
14.5%
9 10
13.2%
5 9
11.8%
7 7
9.2%
2 5
6.6%
4 5
6.6%
, 4
 
5.3%
8 4
 
5.3%
6 2
 
2.6%
Other values (5) 7
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.9%
0 11
16.4%
9 10
14.9%
5 9
13.4%
7 7
10.4%
2 5
7.5%
4 5
7.5%
8 4
 
6.0%
6 2
 
3.0%
3 2
 
3.0%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.4%
0 11
15.1%
9 10
13.7%
5 9
12.3%
7 7
9.6%
2 5
6.8%
4 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 2
 
2.7%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.4%
0 11
15.1%
9 10
13.7%
5 9
12.3%
7 7
9.6%
2 5
6.8%
4 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 2
 
2.7%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:01.194319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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 row화정3동
2nd row4,466
3rd row9,459
4th row32
5th row11
ValueCountFrequency (%)
0 8
24.2%
11 2
 
6.1%
48 2
 
6.1%
32 2
 
6.1%
25 1
 
3.0%
50 1
 
3.0%
9,442 1
 
3.0%
4,461 1
 
3.0%
2 1
 
3.0%
17 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:22:02.103082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
4 11
15.3%
2 8
11.1%
3 7
9.7%
1 6
8.3%
8 5
6.9%
9 5
6.9%
, 4
 
5.6%
5 4
 
5.6%
6 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
0 11
17.7%
4 11
17.7%
2 8
12.9%
3 7
11.3%
1 6
9.7%
8 5
8.1%
9 5
8.1%
5 4
 
6.5%
6 3
 
4.8%
7 2
 
3.2%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
4 11
15.9%
2 8
11.6%
3 7
10.1%
1 6
8.7%
8 5
7.2%
9 5
7.2%
, 4
 
5.8%
5 4
 
5.8%
6 3
 
4.3%
Other values (2) 5
7.2%
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 11
15.9%
4 11
15.9%
2 8
11.6%
3 7
10.1%
1 6
8.7%
8 5
7.2%
9 5
7.2%
, 4
 
5.8%
5 4
 
5.8%
6 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:02.455491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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

Unique21 ?
Unique (%)63.6%

Sample

1st row화정4동
2nd row8,121
3rd row19,319
4th row23
5th row16
ValueCountFrequency (%)
0 8
24.2%
23 2
 
6.1%
16 2
 
6.1%
80 1
 
3.0%
19,319 1
 
3.0%
109 1
 
3.0%
8,148 1
 
3.0%
69 1
 
3.0%
27 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:22:03.174179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.0%
0 13
16.0%
2 8
9.9%
3 8
9.9%
8 7
8.6%
6 6
 
7.4%
9 6
 
7.4%
4 5
 
6.2%
, 4
 
4.9%
5 2
 
2.5%
Other values (4) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
91.4%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.0%
0 13
17.6%
2 8
10.8%
3 8
10.8%
8 7
9.5%
6 6
 
8.1%
9 6
 
8.1%
4 5
 
6.8%
5 2
 
2.7%
7 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.8%
0 13
16.7%
2 8
10.3%
3 8
10.3%
8 7
9.0%
6 6
 
7.7%
9 6
 
7.7%
4 5
 
6.4%
, 4
 
5.1%
5 2
 
2.6%
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 (%)
1 17
21.8%
0 13
16.7%
2 8
10.3%
3 8
10.3%
8 7
9.0%
6 6
 
7.7%
9 6
 
7.7%
4 5
 
6.4%
, 4
 
5.1%
5 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:03.558436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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 row서창동
2nd row2,669
3rd row5,688
4th row9
5th row4
ValueCountFrequency (%)
0 7
21.2%
16 2
 
6.1%
1 2
 
6.1%
4 2
 
6.1%
31 1
 
3.0%
33 1
 
3.0%
5,677 1
 
3.0%
2,655 1
 
3.0%
11 1
 
3.0%
14 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:22:04.470496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.2%
1 9
13.2%
6 8
11.8%
2 7
10.3%
5 7
10.3%
3 5
7.4%
4 4
5.9%
, 4
5.9%
7 4
5.9%
8 3
 
4.4%
Other values (5) 8
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
85.3%
Other Punctuation 4
 
5.9%
Dash Punctuation 3
 
4.4%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.5%
1 9
15.5%
6 8
13.8%
2 7
12.1%
5 7
12.1%
3 5
8.6%
4 4
6.9%
7 4
6.9%
8 3
 
5.2%
9 2
 
3.4%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.8%
1 9
13.8%
6 8
12.3%
2 7
10.8%
5 7
10.8%
3 5
7.7%
4 4
6.2%
, 4
6.2%
7 4
6.2%
8 3
 
4.6%
Other values (2) 5
7.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.8%
1 9
13.8%
6 8
12.3%
2 7
10.8%
5 7
10.8%
3 5
7.7%
4 4
6.2%
, 4
6.2%
7 4
6.2%
8 3
 
4.6%
Other values (2) 5
7.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:04.830819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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 row금호1동
2nd row8,938
3rd row19,856
4th row34
5th row4
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
4 2
 
6.1%
75 1
 
3.0%
77 1
 
3.0%
19,798 1
 
3.0%
8,926 1
 
3.0%
3 1
 
3.0%
58 1
 
3.0%
53 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:22:05.634706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.2%
1 8
10.5%
2 8
10.5%
3 8
10.5%
5 7
9.2%
4 6
7.9%
8 6
7.9%
9 5
6.6%
7 5
6.6%
, 4
 
5.3%
Other values (5) 9
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
86.8%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.2%
1 8
12.1%
2 8
12.1%
3 8
12.1%
5 7
10.6%
4 6
9.1%
8 6
9.1%
9 5
7.6%
7 5
7.6%
6 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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
13.7%
1 8
11.0%
2 8
11.0%
3 8
11.0%
5 7
9.6%
4 6
8.2%
8 6
8.2%
9 5
6.8%
7 5
6.8%
, 4
 
5.5%
Other values (2) 6
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
13.7%
1 8
11.0%
2 8
11.0%
3 8
11.0%
5 7
9.6%
4 6
8.2%
8 6
8.2%
9 5
6.8%
7 5
6.8%
, 4
 
5.5%
Other values (2) 6
8.2%
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
2024-02-10T07:22:05.995023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique21 ?
Unique (%)63.6%

Sample

1st row금호2동
2nd row10,482
3rd row27,364
4th row21
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
21 2
 
6.1%
3 2
 
6.1%
97 1
 
3.0%
27,364 1
 
3.0%
198 1
 
3.0%
10,492 1
 
3.0%
6 1
 
3.0%
102 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:22:06.910822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
19.2%
1 14
17.9%
2 8
10.3%
3 7
9.0%
9 6
 
7.7%
7 5
 
6.4%
6 5
 
6.4%
, 4
 
5.1%
4 4
 
5.1%
8 3
 
3.8%
Other values (5) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
21.4%
1 14
20.0%
2 8
11.4%
3 7
10.0%
9 6
 
8.6%
7 5
 
7.1%
6 5
 
7.1%
4 4
 
5.7%
8 3
 
4.3%
5 3
 
4.3%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
20.0%
1 14
18.7%
2 8
10.7%
3 7
9.3%
9 6
 
8.0%
7 5
 
6.7%
6 5
 
6.7%
, 4
 
5.3%
4 4
 
5.3%
8 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 (%)
0 15
20.0%
1 14
18.7%
2 8
10.7%
3 7
9.3%
9 6
 
8.0%
7 5
 
6.7%
6 5
 
6.7%
, 4
 
5.3%
4 4
 
5.3%
8 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:07.541147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
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 row풍암동
2nd row15,094
3rd row35,357
4th row76
5th row22
ValueCountFrequency (%)
0 5
 
15.2%
2 2
 
6.1%
22 2
 
6.1%
5 1
 
3.0%
296 1
 
3.0%
35,307 1
 
3.0%
15,086 1
 
3.0%
50 1
 
3.0%
8 1
 
3.0%
10 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:22:08.973304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
16.7%
1 13
15.5%
5 11
13.1%
0 10
11.9%
9 5
 
6.0%
4 5
 
6.0%
3 5
 
6.0%
7 5
 
6.0%
, 4
 
4.8%
6 4
 
4.8%
Other values (5) 8
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
89.3%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
18.7%
1 13
17.3%
5 11
14.7%
0 10
13.3%
9 5
 
6.7%
4 5
 
6.7%
3 5
 
6.7%
7 5
 
6.7%
6 4
 
5.3%
8 3
 
4.0%
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 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
17.3%
1 13
16.0%
5 11
13.6%
0 10
12.3%
9 5
 
6.2%
4 5
 
6.2%
3 5
 
6.2%
7 5
 
6.2%
, 4
 
4.9%
6 4
 
4.9%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
17.3%
1 13
16.0%
5 11
13.6%
0 10
12.3%
9 5
 
6.2%
4 5
 
6.2%
3 5
 
6.2%
7 5
 
6.2%
, 4
 
4.9%
6 4
 
4.9%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:22:09.530089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters13
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 row동천동
2nd row6,352
3rd row15,728
4th row17
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
58 2
 
6.1%
42 2
 
6.1%
25 1
 
3.0%
116 1
 
3.0%
16 1
 
3.0%
15,686 1
 
3.0%
6,347 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:22:10.816741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
13.9%
1 9
12.5%
0 8
11.1%
6 8
11.1%
2 8
11.1%
8 5
6.9%
7 5
6.9%
4 5
6.9%
, 4
 
5.6%
3 4
 
5.6%
Other values (3) 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 (%)
5 10
16.1%
1 9
14.5%
0 8
12.9%
6 8
12.9%
2 8
12.9%
8 5
8.1%
7 5
8.1%
4 5
8.1%
3 4
 
6.5%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 (%)
5 10
14.5%
1 9
13.0%
0 8
11.6%
6 8
11.6%
2 8
11.6%
8 5
7.2%
7 5
7.2%
4 5
7.2%
, 4
 
5.8%
3 4
 
5.8%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10
14.5%
1 9
13.0%
0 8
11.6%
6 8
11.6%
2 8
11.6%
8 5
7.2%
7 5
7.2%
4 5
7.2%
, 4
 
5.8%
3 4
 
5.8%
Hangul
ValueCountFrequency (%)
2
66.7%
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: 24
0<NA>행정기관 :<NA>광주광역시 서구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.05.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.04 현재<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 계양동양3동농성1동농성2동광천동유덕동<NA>치평동상무1동상무2동화정1동화정2동화정3동화정4동서창동금호1동금호2동풍암동동천동
3<NA>전월말세대수<NA><NA><NA>133,9351,9722,1416,5562,8673,9974,859<NA>13,59412,24312,9808,6957,9094,4668,1212,6698,93810,48215,0946,352
4<NA>전월말인구수<NA><NA><NA>286,8263,3964,36811,4114,5927,51110,606<NA>29,38924,22622,95115,66419,9419,45919,3195,68819,85627,36435,35715,728
5<NA>전월말거주불명자수<NA><NA><NA>837273042456320<NA>5716310345303223934217617
6<NA>전월말재외국민등록자수<NA><NA><NA>1543160133<NA>1610861611164410225
7<NA>증 가 요 인전 입<NA>2,4892324167414078<NA>262258205184155882955710419124176
8<NA><NA><NA>남자<NA>1,264131380172541<NA>12413910595774813430549812942
9<NA><NA><NA>여자<NA>1,225101187241537<NA>13811910089784016127509311234
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: 24
25<NA><NA>말소<NA><NA>0000000<NA>000000000000
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>2000000<NA>000000000020
28<NA>세대수증감<NA><NA><NA>65-11-617-6-15-7<NA>4715151211-527-14-1210-8-5
29<NA>인구수증감<NA><NA><NA>-252-16-1319-16-41-17<NA>3-32-259-11-1769-11-58-3-50-42
30<NA>거주불명자수증감<NA><NA><NA>-11-201-102<NA>1-600-1-20-1-302-1
31<NA>금월말세대수<NA><NA><NA>134,0001,9612,1356,5732,8613,9824,852<NA>13,64112,25812,9958,7077,9204,4618,1482,6558,92610,49215,0866,347
32<NA>금월말인구수<NA><NA><NA>286,5743,3804,35511,4304,5767,47010,589<NA>29,39224,19422,92615,67319,9309,44219,3885,67719,79827,36135,30715,686
33<NA>금월말거주불명자수<NA><NA><NA>826253043446322<NA>5815710345293023831217816
34<NA>금월말재외국민등록자수<NA><NA><NA>1573160133<NA>1811861511164410226