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

Description2024-02-01
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 07:27:31.581998
Analysis finished2024-02-10 07:27:32.734805
Duration1.15 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

인구이동보고서(1호)
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T07:27:32.979344image/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 (%)
요 2
 
7.7%
인 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%
소 1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T07:27:33.878839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
수 11
 
8.7%
말 8
 
6.3%
월 8
 
6.3%
인 5
 
4.0%
자 5
 
4.0%
전 4
 
3.2%
감 4
 
3.2%
증 4
 
3.2%
금 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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
2024-02-10T07:27:34.318686image/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%
전 2
15.4%
입 1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
출 1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T07:27:35.190273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
국 2
 
7.7%
기 2
 
7.7%
타 2
 
7.7%
전 2
 
7.7%
외 2
 
7.7%
출 2
 
7.7%
록 1
 
3.8%
말 1
 
3.8%
망 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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
2024-02-10T07:27:35.629663image/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 row2023.11 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 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%
2023.11 1
7.1%
현재 1
7.1%
2024-02-10T07:27:36.351549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
 
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
남 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 (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 2
33.3%
3 1
16.7%
0 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 (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
0 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
0 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:27:36.643716image/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%
2024-02-10T07:27:37.320395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Unnamed: 5
Text

MISSING 

Distinct30
Distinct (%)90.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:37.717657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6060606
Min length1

Characters and Unicode

Total characters119
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

Unique28 ?
Unique (%)84.8%

Sample

1st row합 계
2nd row134,154
3rd row284,870
4th row737
5th row166
ValueCountFrequency (%)
0 3
 
8.8%
852 2
 
5.9%
1,533 1
 
2.9%
1,474 1
 
2.9%
866 1
 
2.9%
284,355 1
 
2.9%
133,907 1
 
2.9%
129 1
 
2.9%
515 1
 
2.9%
247 1
 
2.9%
Other values (21) 21
61.8%
2024-02-10T07:27:38.619883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
14.3%
5 13
10.9%
2 12
10.1%
3 12
10.1%
, 11
9.2%
8 10
8.4%
4 10
8.4%
7 9
7.6%
0 8
6.7%
6 6
 
5.0%
Other values (5) 11
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
85.7%
Other Punctuation 11
 
9.2%
Space Separator 2
 
1.7%
Dash Punctuation 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
16.7%
5 13
12.7%
2 12
11.8%
3 12
11.8%
8 10
9.8%
4 10
9.8%
7 9
8.8%
0 8
7.8%
6 6
 
5.9%
9 5
 
4.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117
98.3%
Hangul 2
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
14.5%
5 13
11.1%
2 12
10.3%
3 12
10.3%
, 11
9.4%
8 10
8.5%
4 10
8.5%
7 9
7.7%
0 8
6.8%
6 6
 
5.1%
Other values (3) 9
7.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
98.3%
Hangul 2
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
14.5%
5 13
11.1%
2 12
10.3%
3 12
10.3%
, 11
9.4%
8 10
8.5%
4 10
8.5%
7 9
7.7%
0 8
6.8%
6 6
 
5.1%
Other values (3) 9
7.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:38.931465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8787879
Min length1

Characters and Unicode

Total characters62
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 row양동
2nd row1,905
3rd row3,267
4th row25
5th row3
ValueCountFrequency (%)
0 8
24.2%
13 3
 
9.1%
1 3
 
9.1%
3 2
 
6.1%
14 2
 
6.1%
7 1
 
3.0%
9 1
 
3.0%
3,254 1
 
3.0%
1,901 1
 
3.0%
4 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:27:40.027912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
21.0%
0 10
16.1%
3 7
11.3%
2 6
9.7%
4 4
 
6.5%
7 4
 
6.5%
, 4
 
6.5%
9 3
 
4.8%
5 3
 
4.8%
6 3
 
4.8%
Other values (4) 5
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
87.1%
Other Punctuation 4
 
6.5%
Dash Punctuation 2
 
3.2%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
24.1%
0 10
18.5%
3 7
13.0%
2 6
11.1%
4 4
 
7.4%
7 4
 
7.4%
9 3
 
5.6%
5 3
 
5.6%
6 3
 
5.6%
8 1
 
1.9%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
21.7%
0 10
16.7%
3 7
11.7%
2 6
10.0%
4 4
 
6.7%
7 4
 
6.7%
, 4
 
6.7%
9 3
 
5.0%
5 3
 
5.0%
6 3
 
5.0%
Other values (2) 3
 
5.0%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
21.7%
0 10
16.7%
3 7
11.7%
2 6
10.0%
4 4
 
6.7%
7 4
 
6.7%
, 4
 
6.7%
9 3
 
5.0%
5 3
 
5.0%
6 3
 
5.0%
Other values (2) 3
 
5.0%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:40.495230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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

Unique15 ?
Unique (%)45.5%

Sample

1st row양3동
2nd row2,128
3rd row4,311
4th row29
5th row1
ValueCountFrequency (%)
0 9
27.3%
1 3
 
9.1%
22 2
 
6.1%
19 2
 
6.1%
29 2
 
6.1%
양3동 1
 
3.0%
39 1
 
3.0%
17 1
 
3.0%
4,311 1
 
3.0%
14 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:27:41.650926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
20.3%
1 12
18.8%
0 10
15.6%
9 6
9.4%
4 6
9.4%
3 5
 
7.8%
, 4
 
6.2%
7 2
 
3.1%
8 2
 
3.1%
- 1
 
1.6%
Other values (3) 3
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
89.1%
Other Punctuation 4
 
6.2%
Other Letter 2
 
3.1%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
22.8%
1 12
21.1%
0 10
17.5%
9 6
10.5%
4 6
10.5%
3 5
 
8.8%
7 2
 
3.5%
8 2
 
3.5%
6 1
 
1.8%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
21.0%
1 12
19.4%
0 10
16.1%
9 6
9.7%
4 6
9.7%
3 5
 
8.1%
, 4
 
6.5%
7 2
 
3.2%
8 2
 
3.2%
- 1
 
1.6%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
21.0%
1 12
19.4%
0 10
16.1%
9 6
9.7%
4 6
9.7%
3 5
 
8.1%
, 4
 
6.5%
7 2
 
3.2%
8 2
 
3.2%
- 1
 
1.6%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:42.168314image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성1동
2nd row6,662
3rd row11,559
4th row41
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
41 2
 
6.1%
87 2
 
6.1%
3 1
 
3.0%
11,559 1
 
3.0%
52 1
 
3.0%
11,575 1
 
3.0%
6,664 1
 
3.0%
12 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:27:43.009702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.7%
6 12
16.7%
7 9
12.5%
0 7
9.7%
5 7
9.7%
2 5
6.9%
4 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
3 4
 
5.6%
Other values (4) 4
 
5.6%

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 12
18.5%
6 12
18.5%
7 9
13.8%
0 7
10.8%
5 7
10.8%
2 5
7.7%
4 4
 
6.2%
8 4
 
6.2%
3 4
 
6.2%
9 1
 
1.5%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 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 12
17.4%
6 12
17.4%
7 9
13.0%
0 7
10.1%
5 7
10.1%
2 5
7.2%
4 4
 
5.8%
8 4
 
5.8%
, 4
 
5.8%
3 4
 
5.8%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.4%
6 12
17.4%
7 9
13.0%
0 7
10.1%
5 7
10.1%
2 5
7.2%
4 4
 
5.8%
8 4
 
5.8%
, 4
 
5.8%
3 4
 
5.8%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:43.539485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성2동
2nd row2,863
3rd row4,552
4th row31
5th row1
ValueCountFrequency (%)
0 8
24.2%
23 2
 
6.1%
12 2
 
6.1%
31 2
 
6.1%
1 2
 
6.1%
27 1
 
3.0%
39 1
 
3.0%
4,521 1
 
3.0%
2,841 1
 
3.0%
22 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:27:44.406640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
21.1%
1 10
14.1%
0 8
11.3%
3 8
11.3%
4 6
 
8.5%
5 5
 
7.0%
7 4
 
5.6%
, 4
 
5.6%
8 2
 
2.8%
6 2
 
2.8%
Other values (5) 7
9.9%

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 (%)
2 15
24.2%
1 10
16.1%
0 8
12.9%
3 8
12.9%
4 6
 
9.7%
5 5
 
8.1%
7 4
 
6.5%
8 2
 
3.2%
6 2
 
3.2%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 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 (%)
2 15
22.1%
1 10
14.7%
0 8
11.8%
3 8
11.8%
4 6
 
8.8%
5 5
 
7.4%
7 4
 
5.9%
, 4
 
5.9%
8 2
 
2.9%
6 2
 
2.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
22.1%
1 10
14.7%
0 8
11.8%
3 8
11.8%
4 6
 
8.8%
5 5
 
7.4%
7 4
 
5.9%
, 4
 
5.9%
8 2
 
2.9%
6 2
 
2.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:27:44.854683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4117647
Min length1

Characters and Unicode

Total characters82
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

Unique25 ?
Unique (%)73.5%

Sample

1st row출력일자 :
2nd row광천동
3rd row3,876
4th row7,275
5th row66
ValueCountFrequency (%)
0 5
 
14.3%
12 2
 
5.7%
14 2
 
5.7%
67 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
74 1
 
2.9%
7,164 1
 
2.9%
3,783 1
 
2.9%
32 1
 
2.9%
Other values (19) 19
54.3%
2024-02-10T07:27:45.643682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
14.6%
2 10
12.2%
3 9
11.0%
7 8
9.8%
4 6
7.3%
5 6
7.3%
6 5
 
6.1%
0 5
 
6.1%
, 4
 
4.9%
9 3
 
3.7%
Other values (11) 14
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
80.5%
Other Letter 7
 
8.5%
Other Punctuation 5
 
6.1%
Dash Punctuation 3
 
3.7%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
2 10
15.2%
3 9
13.6%
7 8
12.1%
4 6
9.1%
5 6
9.1%
6 5
7.6%
0 5
7.6%
9 3
 
4.5%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
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 75
91.5%
Hangul 7
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.0%
2 10
13.3%
3 9
12.0%
7 8
10.7%
4 6
8.0%
5 6
8.0%
6 5
6.7%
0 5
6.7%
, 4
 
5.3%
9 3
 
4.0%
Other values (4) 7
9.3%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
91.5%
Hangul 7
 
8.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.0%
2 10
13.3%
3 9
12.0%
7 8
10.7%
4 6
8.0%
5 6
8.0%
6 5
6.7%
0 5
6.7%
, 4
 
5.3%
9 3
 
4.0%
Other values (4) 7
9.3%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:46.097994image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row유덕동
2nd row4,843
3rd row10,513
4th row24
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 3
 
9.1%
24 2
 
6.1%
29 2
 
6.1%
3 2
 
6.1%
31 1
 
3.0%
40 1
 
3.0%
10,475 1
 
3.0%
4,827 1
 
3.0%
38 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:27:47.005996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.9%
2 10
13.9%
4 10
13.9%
1 7
9.7%
3 6
8.3%
5 6
8.3%
7 5
6.9%
8 5
6.9%
, 4
 
5.6%
9 3
 
4.2%
Other values (5) 6
8.3%

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 (%)
0 10
15.9%
2 10
15.9%
4 10
15.9%
1 7
11.1%
3 6
9.5%
5 6
9.5%
7 5
7.9%
8 5
7.9%
9 3
 
4.8%
6 1
 
1.6%
Other Letter
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 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 (%)
0 10
14.5%
2 10
14.5%
4 10
14.5%
1 7
10.1%
3 6
8.7%
5 6
8.7%
7 5
7.2%
8 5
7.2%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.5%
2 10
14.5%
4 10
14.5%
1 7
10.1%
3 6
8.7%
5 6
8.7%
7 5
7.2%
8 5
7.2%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-12-01 00:00:00
Maximum2023-12-01 00:00:00
2024-02-10T07:27:47.372217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:27:47.774143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:48.206613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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 row치평동
2nd row13,810
3rd row29,391
4th row60
5th row19
ValueCountFrequency (%)
0 6
 
18.2%
19 3
 
9.1%
276 1
 
3.0%
29,410 1
 
3.0%
13,811 1
 
3.0%
27 1
 
3.0%
1 1
 
3.0%
23 1
 
3.0%
102 1
 
3.0%
96 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:49.043263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.9%
0 12
14.5%
2 10
12.0%
9 7
 
8.4%
3 7
 
8.4%
8 6
 
7.2%
7 5
 
6.0%
, 4
 
4.8%
6 4
 
4.8%
5 3
 
3.6%
Other values (4) 6
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
91.6%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.0%
0 12
15.8%
2 10
13.2%
9 7
 
9.2%
3 7
 
9.2%
8 6
 
7.9%
7 5
 
6.6%
6 4
 
5.3%
5 3
 
3.9%
4 3
 
3.9%
Other Letter
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.8%
0 12
15.0%
2 10
12.5%
9 7
 
8.8%
3 7
 
8.8%
8 6
 
7.5%
7 5
 
6.2%
, 4
 
5.0%
6 4
 
5.0%
5 3
 
3.8%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
23.8%
0 12
15.0%
2 10
12.5%
9 7
 
8.8%
3 7
 
8.8%
8 6
 
7.5%
7 5
 
6.2%
, 4
 
5.0%
6 4
 
5.0%
5 3
 
3.8%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:49.450594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
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 row상무1동
2nd row12,227
3rd row24,013
4th row120
5th row14
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
166 1
 
3.0%
323 1
 
3.0%
138 1
 
3.0%
23,980 1
 
3.0%
12,220 1
 
3.0%
18 1
 
3.0%
33 1
 
3.0%
7 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:27:51.176787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.5%
2 15
16.9%
0 12
13.5%
3 9
10.1%
8 5
 
5.6%
6 5
 
5.6%
9 4
 
4.5%
, 4
 
4.5%
4 4
 
4.5%
7 3
 
3.4%
Other values (5) 8
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
89.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
25.0%
2 15
18.8%
0 12
15.0%
3 9
11.2%
8 5
 
6.2%
6 5
 
6.2%
9 4
 
5.0%
4 4
 
5.0%
7 3
 
3.8%
5 3
 
3.8%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.3%
2 15
17.4%
0 12
14.0%
3 9
10.5%
8 5
 
5.8%
6 5
 
5.8%
9 4
 
4.7%
, 4
 
4.7%
4 4
 
4.7%
7 3
 
3.5%
Other values (2) 5
 
5.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.3%
2 15
17.4%
0 12
14.0%
3 9
10.5%
8 5
 
5.8%
6 5
 
5.8%
9 4
 
4.7%
, 4
 
4.7%
4 4
 
4.7%
7 3
 
3.5%
Other values (2) 5
 
5.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:51.696032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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 row상무2동
2nd row13,049
3rd row22,756
4th row99
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
111 2
 
6.1%
2 2
 
6.1%
8 2
 
6.1%
81 1
 
3.0%
99 1
 
3.0%
146 1
 
3.0%
22,669 1
 
3.0%
13,023 1
 
3.0%
19 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:27:53.355470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
25.6%
2 12
14.0%
0 11
12.8%
6 8
 
9.3%
9 6
 
7.0%
8 5
 
5.8%
5 4
 
4.7%
, 4
 
4.7%
3 4
 
4.7%
4 3
 
3.5%
Other values (5) 7
 
8.1%

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 22
28.6%
2 12
15.6%
0 11
14.3%
6 8
 
10.4%
9 6
 
7.8%
8 5
 
6.5%
5 4
 
5.2%
3 4
 
5.2%
4 3
 
3.9%
7 2
 
2.6%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 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 22
26.5%
2 12
14.5%
0 11
13.3%
6 8
 
9.6%
9 6
 
7.2%
8 5
 
6.0%
5 4
 
4.8%
, 4
 
4.8%
3 4
 
4.8%
4 3
 
3.6%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
26.5%
2 12
14.5%
0 11
13.3%
6 8
 
9.6%
9 6
 
7.2%
8 5
 
6.0%
5 4
 
4.8%
, 4
 
4.8%
3 4
 
4.8%
4 3
 
3.6%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:53.947532image/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 row화정1동
2nd row8,713
3rd row15,595
4th row44
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
6 3
 
9.1%
126 1
 
3.0%
15,520 1
 
3.0%
8,660 1
 
3.0%
16 1
 
3.0%
75 1
 
3.0%
53 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:54.910735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.7%
6 12
15.4%
0 10
12.8%
7 7
9.0%
5 7
9.0%
8 5
 
6.4%
2 4
 
5.1%
3 4
 
5.1%
, 4
 
5.1%
4 4
 
5.1%
Other values (5) 8
10.3%

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 13
18.8%
6 12
17.4%
0 10
14.5%
7 7
10.1%
5 7
10.1%
8 5
 
7.2%
2 4
 
5.8%
3 4
 
5.8%
4 4
 
5.8%
9 3
 
4.3%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 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 13
17.3%
6 12
16.0%
0 10
13.3%
7 7
9.3%
5 7
9.3%
8 5
 
6.7%
2 4
 
5.3%
3 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.3%
6 12
16.0%
0 10
13.3%
7 7
9.3%
5 7
9.3%
8 5
 
6.7%
2 4
 
5.3%
3 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
Other values (2) 5
 
6.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:55.343529image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row화정2동
2nd row7,914
3rd row19,826
4th row19
5th row15
ValueCountFrequency (%)
0 8
24.2%
7,914 2
 
6.1%
15 2
 
6.1%
167 2
 
6.1%
81 1
 
3.0%
19 1
 
3.0%
96 1
 
3.0%
19,827 1
 
3.0%
3 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:27:56.256335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.7%
0 11
15.3%
7 8
11.1%
6 7
9.7%
9 7
9.7%
5 6
8.3%
2 5
6.9%
, 4
 
5.6%
4 3
 
4.2%
3 3
 
4.2%
Other values (4) 6
8.3%

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 12
18.5%
0 11
16.9%
7 8
12.3%
6 7
10.8%
9 7
10.8%
5 6
9.2%
2 5
7.7%
4 3
 
4.6%
3 3
 
4.6%
8 3
 
4.6%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 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 12
17.4%
0 11
15.9%
7 8
11.6%
6 7
10.1%
9 7
10.1%
5 6
8.7%
2 5
7.2%
, 4
 
5.8%
4 3
 
4.3%
3 3
 
4.3%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.4%
0 11
15.9%
7 8
11.6%
6 7
10.1%
9 7
10.1%
5 6
8.7%
2 5
7.2%
, 4
 
5.8%
4 3
 
4.3%
3 3
 
4.3%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:56.641467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique21 ?
Unique (%)63.6%

Sample

1st row화정3동
2nd row4,414
3rd row9,296
4th row22
5th row12
ValueCountFrequency (%)
0 6
18.2%
20 3
 
9.1%
35 2
 
6.1%
2 2
 
6.1%
12 2
 
6.1%
85 1
 
3.0%
43 1
 
3.0%
9,276 1
 
3.0%
4,412 1
 
3.0%
4 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:27:57.466193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
22.5%
0 10
14.1%
4 8
11.3%
3 7
9.9%
1 5
 
7.0%
5 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
6 3
 
4.2%
7 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 (%)
2 16
25.8%
0 10
16.1%
4 8
12.9%
3 7
11.3%
1 5
 
8.1%
5 4
 
6.5%
9 3
 
4.8%
6 3
 
4.8%
7 3
 
4.8%
8 3
 
4.8%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 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 (%)
2 16
23.5%
0 10
14.7%
4 8
11.8%
3 7
10.3%
1 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
9 3
 
4.4%
6 3
 
4.4%
7 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
23.5%
0 10
14.7%
4 8
11.8%
3 7
10.3%
1 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
9 3
 
4.4%
6 3
 
4.4%
7 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:57.841658image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row화정4동
2nd row8,231
3rd row19,534
4th row12
5th row13
ValueCountFrequency (%)
0 4
 
12.1%
50 2
 
6.1%
1 2
 
6.1%
12 2
 
6.1%
13 2
 
6.1%
69 1
 
3.0%
87 1
 
3.0%
19,515 1
 
3.0%
8,219 1
 
3.0%
4 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:59.155991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
26.0%
0 6
 
7.8%
5 6
 
7.8%
6 6
 
7.8%
4 6
 
7.8%
9 6
 
7.8%
3 5
 
6.5%
8 5
 
6.5%
7 4
 
5.2%
, 4
 
5.2%
Other values (5) 9
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
29.4%
0 6
 
8.8%
5 6
 
8.8%
6 6
 
8.8%
4 6
 
8.8%
9 6
 
8.8%
3 5
 
7.4%
8 5
 
7.4%
7 4
 
5.9%
2 4
 
5.9%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
27.0%
0 6
 
8.1%
5 6
 
8.1%
6 6
 
8.1%
4 6
 
8.1%
9 6
 
8.1%
3 5
 
6.8%
8 5
 
6.8%
7 4
 
5.4%
, 4
 
5.4%
Other values (2) 6
 
8.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
27.0%
0 6
 
8.1%
5 6
 
8.1%
6 6
 
8.1%
4 6
 
8.1%
9 6
 
8.1%
3 5
 
6.8%
8 5
 
6.8%
7 4
 
5.4%
, 4
 
5.4%
Other values (2) 6
 
8.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:59.539772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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

Unique19 ?
Unique (%)57.6%

Sample

1st row서창동
2nd row2,645
3rd row5,662
4th row7
5th row4
ValueCountFrequency (%)
0 6
18.2%
4 3
 
9.1%
1 3
 
9.1%
35 2
 
6.1%
27 1
 
3.0%
7 1
 
3.0%
2,645 1
 
3.0%
5,663 1
 
3.0%
2,647 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:28:00.644837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 9
14.1%
2 8
12.5%
0 7
10.9%
1 6
9.4%
6 6
9.4%
5 5
7.8%
7 5
7.8%
9 5
7.8%
3 4
6.2%
, 4
6.2%
Other values (4) 5
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
89.1%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
15.8%
2 8
14.0%
0 7
12.3%
1 6
10.5%
6 6
10.5%
5 5
8.8%
7 5
8.8%
9 5
8.8%
3 4
7.0%
8 2
 
3.5%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
95.3%
Hangul 3
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
14.8%
2 8
13.1%
0 7
11.5%
1 6
9.8%
6 6
9.8%
5 5
8.2%
7 5
8.2%
9 5
8.2%
3 4
6.6%
, 4
6.6%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
95.3%
Hangul 3
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9
14.8%
2 8
13.1%
0 7
11.5%
1 6
9.8%
6 6
9.8%
5 5
8.2%
7 5
8.2%
9 5
8.2%
3 4
6.6%
, 4
6.6%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:28:01.067313image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row금호1동
2nd row8,900
3rd row19,550
4th row26
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
6 2
 
6.1%
1 2
 
6.1%
73 1
 
3.0%
19,517 1
 
3.0%
8,899 1
 
3.0%
3 1
 
3.0%
33 1
 
3.0%
8 1
 
3.0%
55 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:28:02.006976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
1 9
12.3%
9 8
11.0%
4 7
9.6%
5 7
9.6%
7 5
6.8%
2 5
6.8%
3 5
6.8%
8 4
 
5.5%
, 4
 
5.5%
Other values (5) 8
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
87.7%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 9
14.1%
9 8
12.5%
4 7
10.9%
5 7
10.9%
7 5
7.8%
2 5
7.8%
3 5
7.8%
8 4
 
6.2%
6 3
 
4.7%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 9
12.9%
9 8
11.4%
4 7
10.0%
5 7
10.0%
7 5
7.1%
2 5
7.1%
3 5
7.1%
8 4
 
5.7%
, 4
 
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
1 9
12.9%
9 8
11.4%
4 7
10.0%
5 7
10.0%
7 5
7.1%
2 5
7.1%
3 5
7.1%
8 4
 
5.7%
, 4
 
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:28:02.465253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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

Unique19 ?
Unique (%)57.6%

Sample

1st row금호2동
2nd row10,511
3rd row27,256
4th row23
5th row11
ValueCountFrequency (%)
0 6
18.2%
10 2
 
6.1%
10,511 2
 
6.1%
11 2
 
6.1%
3 2
 
6.1%
48 1
 
3.0%
23 1
 
3.0%
193 1
 
3.0%
27,260 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:28:03.209023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
22.1%
0 13
16.9%
3 8
10.4%
2 7
9.1%
7 6
 
7.8%
9 5
 
6.5%
6 5
 
6.5%
, 4
 
5.2%
5 4
 
5.2%
4 3
 
3.9%
Other values (4) 5
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
90.9%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
24.3%
0 13
18.6%
3 8
11.4%
2 7
10.0%
7 6
 
8.6%
9 5
 
7.1%
6 5
 
7.1%
5 4
 
5.7%
4 3
 
4.3%
8 2
 
2.9%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
23.0%
0 13
17.6%
3 8
10.8%
2 7
9.5%
7 6
 
8.1%
9 5
 
6.8%
6 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
4 3
 
4.1%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
23.0%
0 13
17.6%
3 8
10.8%
2 7
9.5%
7 6
 
8.1%
9 5
 
6.8%
6 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
4 3
 
4.1%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:28:03.690812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
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

Unique27 ?
Unique (%)81.8%

Sample

1st row풍암동
2nd row15,108
3rd row34,999
4th row76
5th row23
ValueCountFrequency (%)
0 4
 
12.1%
23 2
 
6.1%
171 1
 
3.0%
362 1
 
3.0%
34,910 1
 
3.0%
15,090 1
 
3.0%
11 1
 
3.0%
89 1
 
3.0%
18 1
 
3.0%
6 1
 
3.0%
Other values (19) 19
57.6%
2024-02-10T07:28:04.659095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
23.9%
0 12
13.6%
3 9
10.2%
9 9
10.2%
8 6
 
6.8%
6 6
 
6.8%
2 5
 
5.7%
7 5
 
5.7%
, 4
 
4.5%
5 3
 
3.4%
Other values (5) 8
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
89.8%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
26.6%
0 12
15.2%
3 9
11.4%
9 9
11.4%
8 6
 
7.6%
6 6
 
7.6%
2 5
 
6.3%
7 5
 
6.3%
5 3
 
3.8%
4 3
 
3.8%
Other Letter
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
24.7%
0 12
14.1%
3 9
10.6%
9 9
10.6%
8 6
 
7.1%
6 6
 
7.1%
2 5
 
5.9%
7 5
 
5.9%
, 4
 
4.7%
5 3
 
3.5%
Other values (2) 5
 
5.9%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
24.7%
0 12
14.1%
3 9
10.6%
9 9
10.6%
8 6
 
7.1%
6 6
 
7.1%
2 5
 
5.9%
7 5
 
5.9%
, 4
 
4.7%
5 3
 
3.5%
Other values (2) 5
 
5.9%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:28:05.059048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters12
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

Unique18 ?
Unique (%)54.5%

Sample

1st row동천동
2nd row6,355
3rd row15,515
4th row13
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 3
 
9.1%
3 2
 
6.1%
15,515 2
 
6.1%
23 1
 
3.0%
6,356 1
 
3.0%
1 1
 
3.0%
31 1
 
3.0%
58 1
 
3.0%
20 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:28:05.910233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 15
21.7%
0 11
15.9%
1 11
15.9%
3 9
13.0%
6 6
 
8.7%
9 4
 
5.8%
, 4
 
5.8%
2 4
 
5.8%
동 2
 
2.9%
천 1
 
1.4%
Other values (2) 2
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
89.9%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 15
24.2%
0 11
17.7%
1 11
17.7%
3 9
14.5%
6 6
 
9.7%
9 4
 
6.5%
2 4
 
6.5%
4 1
 
1.6%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
5 15
22.7%
0 11
16.7%
1 11
16.7%
3 9
13.6%
6 6
 
9.1%
9 4
 
6.1%
, 4
 
6.1%
2 4
 
6.1%
4 1
 
1.5%
8 1
 
1.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 15
22.7%
0 11
16.7%
1 11
16.7%
3 9
13.6%
6 6
 
9.1%
9 4
 
6.1%
, 4
 
6.1%
2 4
 
6.1%
4 1
 
1.5%
8 1
 
1.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 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>2023.12.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.11 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>134,1541,9052,1286,6622,8633,8764,843<NA>13,81012,22713,0498,7137,9144,4148,2312,6458,90010,51115,1086,355
4<NA>전월말인구수<NA><NA><NA>284,8703,2674,31111,5594,5527,27510,513<NA>29,39124,01322,75615,59519,8269,29619,5345,66219,55027,25634,99915,515
5<NA>전월말거주불명자수<NA><NA><NA>737252941316624<NA>601209944192212726237613
6<NA>전월말재외국민등록자수<NA><NA><NA>1663171122<NA>1914861512134611239
7<NA>증 가 요 인전 입계<NA>2,5732139173475178<NA>3082812261771677314789119193269115
8<NA><NA><NA>남자<NA>1,285131786212249<NA>1561461119177387640499113963
9<NA><NA><NA>여자<NA>1,28882287262929<NA>15213511586903571497010213052
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>540000350<NA>002102311360
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>1000000<NA>000000100000
28<NA>세대수증감<NA><NA><NA>-247-412-22-93-16<NA>1-7-26-530-2-122-10-181
29<NA>인구수증감<NA><NA><NA>-515-13-716-31-111-38<NA>19-33-87-751-20-191-334-890
30<NA>거주불명자수증감<NA><NA><NA>129101223-323<NA>271819163444310113
31<NA>금월말세대수<NA><NA><NA>133,9071,9012,1296,6642,8413,7834,827<NA>13,81112,22013,0238,6607,9144,4128,2192,6478,89910,51115,0906,356
32<NA>금월말인구수<NA><NA><NA>284,3553,2544,30411,5754,5217,16410,475<NA>29,41023,98022,66915,52019,8279,27619,5155,66319,51727,26034,91015,515
33<NA>금월말거주불명자수<NA><NA><NA>866262953543427<NA>87138118602226161129338716
34<NA>금월말재외국민등록자수<NA><NA><NA>1653171122<NA>1913861512134611239