Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text23
DateTime1

Dataset

Description2024-01-26
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

Alerts

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

Reproduction

Analysis started2024-02-10 07:27:01.298927
Analysis finished2024-02-10 07:27:02.381801
Duration1.08 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
2024-02-10T07:27:02.651834image/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%
2024-02-10T07:27:03.425349image/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
2024-02-10T07:27:03.687243image/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%
2024-02-10T07:27:04.410133image/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
2024-02-10T07:27:04.763842image/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 row2023.10 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%
2023.10 1
7.1%
현재 1
7.1%
2024-02-10T07:27:05.468718image/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%
1 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%
1 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%
1 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:27:05.684091image/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%
2024-02-10T07:27:06.269356image/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
2024-02-10T07:27:06.637145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6363636
Min length1

Characters and Unicode

Total characters120
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 row134,405
3rd row285,537
4th row804
5th row162
ValueCountFrequency (%)
0 4
 
11.8%
861 2
 
5.9%
3,152 1
 
2.9%
737 1
 
2.9%
284,870 1
 
2.9%
134,154 1
 
2.9%
67 1
 
2.9%
667 1
 
2.9%
251 1
 
2.9%
57 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:27:07.393986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
15.0%
7 14
11.7%
6 12
10.0%
, 12
10.0%
2 11
9.2%
5 10
8.3%
0 9
7.5%
3 8
6.7%
4 7
 
5.8%
8 6
 
5.0%
Other values (5) 13
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
84.2%
Other Punctuation 12
 
10.0%
Dash Punctuation 3
 
2.5%
Space Separator 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
17.8%
7 14
13.9%
6 12
11.9%
2 11
10.9%
5 10
9.9%
0 9
8.9%
3 8
7.9%
4 7
 
6.9%
8 6
 
5.9%
9 6
 
5.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118
98.3%
Hangul 2
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
15.3%
7 14
11.9%
6 12
10.2%
, 12
10.2%
2 11
9.3%
5 10
8.5%
0 9
7.6%
3 8
6.8%
4 7
 
5.9%
8 6
 
5.1%
Other values (3) 11
9.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
98.3%
Hangul 2
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
15.3%
7 14
11.9%
6 12
10.2%
, 12
10.2%
2 11
9.3%
5 10
8.5%
0 9
7.6%
3 8
6.8%
4 7
 
5.9%
8 6
 
5.1%
Other values (3) 11
9.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:07.704250image/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 categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row양동
2nd row1,911
3rd row3,290
4th row25
5th row3
ValueCountFrequency (%)
0 9
27.3%
6 3
 
9.1%
3 2
 
6.1%
23 2
 
6.1%
25 2
 
6.1%
11 1
 
3.0%
18 1
 
3.0%
1,905 1
 
3.0%
8 1
 
3.0%
24 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:27:08.451928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
17.2%
1 11
17.2%
2 9
14.1%
3 6
9.4%
5 5
7.8%
6 5
7.8%
, 4
 
6.2%
4 3
 
4.7%
9 3
 
4.7%
8 2
 
3.1%
Other values (4) 5
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
87.5%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.6%
1 11
19.6%
2 9
16.1%
3 6
10.7%
5 5
8.9%
6 5
8.9%
4 3
 
5.4%
9 3
 
5.4%
8 2
 
3.6%
7 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 62
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.7%
1 11
17.7%
2 9
14.5%
3 6
9.7%
5 5
8.1%
6 5
8.1%
, 4
 
6.5%
4 3
 
4.8%
9 3
 
4.8%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.7%
1 11
17.7%
2 9
14.5%
3 6
9.7%
5 5
8.1%
6 5
8.1%
, 4
 
6.5%
4 3
 
4.8%
9 3
 
4.8%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:08.767546image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row양3동
2nd row2,130
3rd row4,330
4th row31
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
2 2
 
6.1%
14 2
 
6.1%
5 2
 
6.1%
19 2
 
6.1%
2,130 1
 
3.0%
26 1
 
3.0%
4,311 1
 
3.0%
2,128 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:27:09.587270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
22.7%
2 11
16.7%
0 9
13.6%
4 7
10.6%
3 7
10.6%
, 4
 
6.1%
- 3
 
4.5%
9 3
 
4.5%
5 2
 
3.0%
7 1
 
1.5%
Other values (4) 4
 
6.1%

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 (%)
1 15
26.3%
2 11
19.3%
0 9
15.8%
4 7
12.3%
3 7
12.3%
9 3
 
5.3%
5 2
 
3.5%
7 1
 
1.8%
8 1
 
1.8%
6 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 (%)
1 15
23.4%
2 11
17.2%
0 9
14.1%
4 7
10.9%
3 7
10.9%
, 4
 
6.2%
- 3
 
4.7%
9 3
 
4.7%
5 2
 
3.1%
7 1
 
1.6%
Other values (2) 2
 
3.1%
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 (%)
1 15
23.4%
2 11
17.2%
0 9
14.1%
4 7
10.9%
3 7
10.9%
, 4
 
6.2%
- 3
 
4.7%
9 3
 
4.7%
5 2
 
3.1%
7 1
 
1.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 8
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:09.954708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters14
Distinct 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 row농성1동
2nd row6,687
3rd row11,599
4th row41
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 4
 
12.1%
41 3
 
9.1%
94 2
 
6.1%
48 1
 
3.0%
11,599 1
 
3.0%
54 1
 
3.0%
6,662 1
 
3.0%
40 1
 
3.0%
25 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:27:10.767694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.9%
4 10
13.5%
0 9
12.2%
5 8
10.8%
6 7
9.5%
8 7
9.5%
9 6
8.1%
7 5
6.8%
, 4
 
5.4%
- 2
 
2.7%
Other values (4) 5
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.9%
4 10
15.4%
0 9
13.8%
5 8
12.3%
6 7
10.8%
8 7
10.8%
9 6
9.2%
7 5
7.7%
2 2
 
3.1%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.5%
4 10
14.1%
0 9
12.7%
5 8
11.3%
6 7
9.9%
8 7
9.9%
9 6
8.5%
7 5
7.0%
, 4
 
5.6%
- 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.5%
4 10
14.1%
0 9
12.7%
5 8
11.3%
6 7
9.9%
8 7
9.9%
9 6
8.5%
7 5
7.0%
, 4
 
5.6%
- 2
 
2.8%
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
2024-02-10T07:27:11.064622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성2동
2nd row2,876
3rd row4,547
4th row32
5th row0
ValueCountFrequency (%)
0 8
24.2%
1 3
 
9.1%
31 2
 
6.1%
5 2
 
6.1%
29 1
 
3.0%
32 1
 
3.0%
28 1
 
3.0%
2,863 1
 
3.0%
13 1
 
3.0%
2,876 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:27:11.615474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.3%
3 9
15.3%
1 9
15.3%
2 8
13.6%
5 7
11.9%
7 4
6.8%
6 4
6.8%
4 3
 
5.1%
9 3
 
5.1%
8 3
 
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

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

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:27:11.860686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2941176
Min length1

Characters and Unicode

Total characters78
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

Unique23 ?
Unique (%)67.6%

Sample

1st row출력일자 :
2nd row광천동
3rd row3,902
4th row7,328
5th row65
ValueCountFrequency (%)
0 7
20.0%
12 2
 
5.7%
26 2
 
5.7%
61 2
 
5.7%
1
 
2.9%
111 1
 
2.9%
7,275 1
 
2.9%
3,876 1
 
2.9%
1 1
 
2.9%
53 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T07:27:12.520618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
14.1%
0 10
12.8%
1 10
12.8%
6 9
11.5%
5 7
9.0%
3 6
7.7%
, 4
 
5.1%
7 4
 
5.1%
9 2
 
2.6%
8 2
 
2.6%
Other values (11) 13
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
80.8%
Other Letter 7
 
9.0%
Other Punctuation 5
 
6.4%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
17.5%
0 10
15.9%
1 10
15.9%
6 9
14.3%
5 7
11.1%
3 6
9.5%
7 4
 
6.3%
9 2
 
3.2%
8 2
 
3.2%
4 2
 
3.2%
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 71
91.0%
Hangul 7
 
9.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
15.5%
0 10
14.1%
1 10
14.1%
6 9
12.7%
5 7
9.9%
3 6
8.5%
, 4
 
5.6%
7 4
 
5.6%
9 2
 
2.8%
8 2
 
2.8%
Other values (4) 6
8.5%
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 71
91.0%
Hangul 7
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
15.5%
0 10
14.1%
1 10
14.1%
6 9
12.7%
5 7
9.9%
3 6
8.5%
, 4
 
5.6%
7 4
 
5.6%
9 2
 
2.8%
8 2
 
2.8%
Other values (4) 6
8.5%
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 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:12.760238image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row유덕동
2nd row4,858
3rd row10,551
4th row24
5th row3
ValueCountFrequency (%)
0 8
24.2%
24 2
 
6.1%
57 1
 
3.0%
116 1
 
3.0%
10,513 1
 
3.0%
4,843 1
 
3.0%
38 1
 
3.0%
15 1
 
3.0%
6 1
 
3.0%
39 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:27:13.647753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
1 9
12.5%
4 7
9.7%
5 7
9.7%
3 7
9.7%
8 6
8.3%
2 5
6.9%
7 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
Other values (5) 8
11.1%

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 11
17.5%
1 9
14.3%
4 7
11.1%
5 7
11.1%
3 7
11.1%
8 6
9.5%
2 5
7.9%
7 4
 
6.3%
9 4
 
6.3%
6 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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
1 9
13.0%
4 7
10.1%
5 7
10.1%
3 7
10.1%
8 6
8.7%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
9 4
 
5.8%
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%
1 9
13.0%
4 7
10.1%
5 7
10.1%
3 7
10.1%
8 6
8.7%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
9 4
 
5.8%
Other values (2) 5
7.2%
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
Minimum2023-11-03 00:00:00
Maximum2023-11-03 00:00:00
2024-02-10T07:27:13.945870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:27:14.260330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:14.564892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

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

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row치평동
2nd row13,812
3rd row29,439
4th row58
5th row17
ValueCountFrequency (%)
0 6
 
18.2%
2 2
 
6.1%
164 1
 
3.0%
349 1
 
3.0%
60 1
 
3.0%
29,391 1
 
3.0%
13,810 1
 
3.0%
48 1
 
3.0%
11 1
 
3.0%
131 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:27:15.277035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.5%
0 10
11.8%
3 9
10.6%
8 7
 
8.2%
2 7
 
8.2%
9 7
 
8.2%
4 7
 
8.2%
, 4
 
4.7%
6 4
 
4.7%
5 3
 
3.5%
Other values (5) 7
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
89.4%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
26.3%
0 10
13.2%
3 9
11.8%
8 7
 
9.2%
2 7
 
9.2%
9 7
 
9.2%
4 7
 
9.2%
6 4
 
5.3%
5 3
 
3.9%
7 2
 
2.6%
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 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
24.4%
0 10
12.2%
3 9
11.0%
8 7
 
8.5%
2 7
 
8.5%
9 7
 
8.5%
4 7
 
8.5%
, 4
 
4.9%
6 4
 
4.9%
5 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
24.4%
0 10
12.2%
3 9
11.0%
8 7
 
8.5%
2 7
 
8.5%
9 7
 
8.5%
4 7
 
8.5%
, 4
 
4.9%
6 4
 
4.9%
5 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:15.595044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7575758
Min length1

Characters and Unicode

Total characters91
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 row12,254
3rd row24,047
4th row151
5th row14
ValueCountFrequency (%)
0 5
 
15.2%
14 3
 
9.1%
27 2
 
6.1%
280 1
 
3.0%
24,013 1
 
3.0%
12,227 1
 
3.0%
31 1
 
3.0%
34 1
 
3.0%
100 1
 
3.0%
110 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:16.661712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
20.9%
0 14
15.4%
4 13
14.3%
2 12
13.2%
7 8
8.8%
3 6
 
6.6%
, 4
 
4.4%
5 4
 
4.4%
- 3
 
3.3%
9 2
 
2.2%
Other values (5) 6
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
89.0%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
23.5%
0 14
17.3%
4 13
16.0%
2 12
14.8%
7 8
9.9%
3 6
 
7.4%
5 4
 
4.9%
9 2
 
2.5%
8 2
 
2.5%
6 1
 
1.2%
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 88
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
21.6%
0 14
15.9%
4 13
14.8%
2 12
13.6%
7 8
9.1%
3 6
 
6.8%
, 4
 
4.5%
5 4
 
4.5%
- 3
 
3.4%
9 2
 
2.3%
Other values (2) 3
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
21.6%
0 14
15.9%
4 13
14.8%
2 12
13.6%
7 8
9.1%
3 6
 
6.8%
, 4
 
4.5%
5 4
 
4.5%
- 3
 
3.4%
9 2
 
2.3%
Other values (2) 3
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:17.079815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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 row상무2동
2nd row13,051
3rd row22,808
4th row106
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
138 2
 
6.1%
2 2
 
6.1%
8 2
 
6.1%
79 1
 
3.0%
276 1
 
3.0%
22,756 1
 
3.0%
13,049 1
 
3.0%
7 1
 
3.0%
52 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:27:18.033021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
16.9%
1 12
14.5%
0 11
13.3%
8 9
10.8%
3 6
7.2%
7 6
7.2%
6 5
 
6.0%
, 4
 
4.8%
5 4
 
4.8%
9 4
 
4.8%
Other values (5) 8
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
88.0%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
19.2%
1 12
16.4%
0 11
15.1%
8 9
12.3%
3 6
8.2%
7 6
8.2%
6 5
 
6.8%
5 4
 
5.5%
9 4
 
5.5%
4 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
17.5%
1 12
15.0%
0 11
13.8%
8 9
11.2%
3 6
7.5%
7 6
7.5%
6 5
 
6.2%
, 4
 
5.0%
5 4
 
5.0%
9 4
 
5.0%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
17.5%
1 12
15.0%
0 11
13.8%
8 9
11.2%
3 6
7.5%
7 6
7.5%
6 5
 
6.2%
, 4
 
5.0%
5 4
 
5.0%
9 4
 
5.0%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:18.461166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique23 ?
Unique (%)69.7%

Sample

1st row화정1동
2nd row8,748
3rd row15,648
4th row46
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
68 2
 
6.1%
6 2
 
6.1%
105 1
 
3.0%
119 1
 
3.0%
15,595 1
 
3.0%
8,713 1
 
3.0%
2 1
 
3.0%
53 1
 
3.0%
35 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:19.371105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.3%
5 11
13.6%
0 7
8.6%
6 7
8.6%
2 7
8.6%
8 6
7.4%
4 6
7.4%
9 5
 
6.2%
, 4
 
4.9%
7 4
 
4.9%
Other values (5) 10
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
87.7%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
19.7%
5 11
15.5%
0 7
9.9%
6 7
9.9%
2 7
9.9%
8 6
8.5%
4 6
8.5%
9 5
 
7.0%
7 4
 
5.6%
3 4
 
5.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.9%
5 11
14.1%
0 7
9.0%
6 7
9.0%
2 7
9.0%
8 6
7.7%
4 6
7.7%
9 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
Other values (2) 7
9.0%
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 14
17.9%
5 11
14.1%
0 7
9.0%
6 7
9.0%
2 7
9.0%
8 6
7.7%
4 6
7.7%
9 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
Other values (2) 7
9.0%
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
2024-02-10T07:27:19.878454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique23 ?
Unique (%)69.7%

Sample

1st row화정2동
2nd row7,935
3rd row19,911
4th row28
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
11 2
 
6.1%
15 2
 
6.1%
111 1
 
3.0%
101 1
 
3.0%
19,826 1
 
3.0%
7,914 1
 
3.0%
9 1
 
3.0%
85 1
 
3.0%
21 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:20.686720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
28.4%
0 8
 
9.9%
9 8
 
9.9%
5 7
 
8.6%
2 7
 
8.6%
7 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
8 4
 
4.9%
6 3
 
3.7%
Other values (5) 7
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
87.7%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
32.4%
0 8
 
11.3%
9 8
 
11.3%
5 7
 
9.9%
2 7
 
9.9%
7 5
 
7.0%
4 5
 
7.0%
8 4
 
5.6%
6 3
 
4.2%
3 1
 
1.4%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
29.5%
0 8
 
10.3%
9 8
 
10.3%
5 7
 
9.0%
2 7
 
9.0%
7 5
 
6.4%
4 5
 
6.4%
, 4
 
5.1%
8 4
 
5.1%
6 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
29.5%
0 8
 
10.3%
9 8
 
10.3%
5 7
 
9.0%
2 7
 
9.0%
7 5
 
6.4%
4 5
 
6.4%
, 4
 
5.1%
8 4
 
5.1%
6 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:20.921680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row화정3동
2nd row4,417
3rd row9,312
4th row23
5th row12
ValueCountFrequency (%)
0 7
21.2%
45 2
 
6.1%
38 2
 
6.1%
12 2
 
6.1%
1 2
 
6.1%
27 1
 
3.0%
43 1
 
3.0%
9,296 1
 
3.0%
4,414 1
 
3.0%
16 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:27:21.577150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
16.4%
1 10
13.7%
0 8
11.0%
2 8
11.0%
3 8
11.0%
9 6
8.2%
, 4
 
5.5%
5 3
 
4.1%
8 3
 
4.1%
7 3
 
4.1%
Other values (5) 8
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
86.3%
Other Punctuation 4
 
5.5%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
19.0%
1 10
15.9%
0 8
12.7%
2 8
12.7%
3 8
12.7%
9 6
9.5%
5 3
 
4.8%
8 3
 
4.8%
7 3
 
4.8%
6 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
17.1%
1 10
14.3%
0 8
11.4%
2 8
11.4%
3 8
11.4%
9 6
8.6%
, 4
 
5.7%
5 3
 
4.3%
8 3
 
4.3%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
17.1%
1 10
14.3%
0 8
11.4%
2 8
11.4%
3 8
11.4%
9 6
8.6%
, 4
 
5.7%
5 3
 
4.3%
8 3
 
4.3%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:21.831308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row화정4동
2nd row8,237
3rd row19,552
4th row20
5th row13
ValueCountFrequency (%)
0 6
 
18.2%
13 2
 
6.1%
102 1
 
3.0%
75 1
 
3.0%
19,534 1
 
3.0%
8,231 1
 
3.0%
8 1
 
3.0%
18 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:27:22.334844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.7%
0 10
12.8%
5 8
10.3%
3 7
9.0%
9 7
9.0%
8 6
7.7%
2 6
7.7%
7 5
 
6.4%
, 4
 
5.1%
6 3
 
3.8%
Other values (5) 9
11.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 10
14.7%
5 8
11.8%
3 7
10.3%
9 7
10.3%
8 6
8.8%
2 6
8.8%
7 5
 
7.4%
6 3
 
4.4%
4 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.3%
0 10
13.3%
5 8
10.7%
3 7
9.3%
9 7
9.3%
8 6
8.0%
2 6
8.0%
7 5
 
6.7%
, 4
 
5.3%
6 3
 
4.0%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.3%
0 10
13.3%
5 8
10.7%
3 7
9.3%
9 7
9.3%
8 6
8.0%
2 6
8.0%
7 5
 
6.7%
, 4
 
5.3%
6 3
 
4.0%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:22.679813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

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

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row서창동
2nd row2,657
3rd row5,679
4th row7
5th row4
ValueCountFrequency (%)
0 9
27.3%
4 3
 
9.1%
7 2
 
6.1%
32 2
 
6.1%
72 1
 
3.0%
2,645 1
 
3.0%
17 1
 
3.0%
12 1
 
3.0%
26 1
 
3.0%
14 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:27:23.223180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.9%
2 10
14.9%
6 7
10.4%
4 6
9.0%
7 6
9.0%
3 5
7.5%
5 5
7.5%
1 5
7.5%
, 4
 
6.0%
9 2
 
3.0%
Other values (5) 7
10.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
17.2%
2 10
17.2%
6 7
12.1%
4 6
10.3%
7 6
10.3%
3 5
8.6%
5 5
8.6%
1 5
8.6%
9 2
 
3.4%
8 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.6%
2 10
15.6%
6 7
10.9%
4 6
9.4%
7 6
9.4%
3 5
7.8%
5 5
7.8%
1 5
7.8%
, 4
 
6.2%
9 2
 
3.1%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.6%
2 10
15.6%
6 7
10.9%
4 6
9.4%
7 6
9.4%
3 5
7.8%
5 5
7.8%
1 5
7.8%
, 4
 
6.2%
9 2
 
3.1%
Other values (2) 4
 
6.2%
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
2024-02-10T07:27:23.472475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row금호1동
2nd row8,908
3rd row19,598
4th row29
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
6 2
 
6.1%
29 2
 
6.1%
49 1
 
3.0%
79 1
 
3.0%
19,550 1
 
3.0%
8,900 1
 
3.0%
3 1
 
3.0%
48 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:27:24.138226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
9 9
12.0%
1 9
12.0%
4 8
10.7%
5 7
9.3%
8 7
9.3%
6 6
8.0%
2 5
6.7%
, 4
 
5.3%
- 3
 
4.0%
Other values (5) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.9%
9 9
13.8%
1 9
13.8%
4 8
12.3%
5 7
10.8%
8 7
10.8%
6 6
9.2%
2 5
7.7%
7 2
 
3.1%
3 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
9 9
12.5%
1 9
12.5%
4 8
11.1%
5 7
9.7%
8 7
9.7%
6 6
8.3%
2 5
6.9%
, 4
 
5.6%
- 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.3%
9 9
12.5%
1 9
12.5%
4 8
11.1%
5 7
9.7%
8 7
9.7%
6 6
8.3%
2 5
6.9%
, 4
 
5.6%
- 3
 
4.2%
Other values (2) 3
 
4.2%
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
2024-02-10T07:27:24.387088image/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 row금호2동
2nd row10,532
3rd row27,300
4th row23
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
23 2
 
6.1%
86 2
 
6.1%
115 1
 
3.0%
27,300 1
 
3.0%
196 1
 
3.0%
10,511 1
 
3.0%
44 1
 
3.0%
21 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:27:25.209608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.0%
0 11
13.6%
2 10
12.3%
3 7
8.6%
5 6
 
7.4%
6 5
 
6.2%
9 5
 
6.2%
8 4
 
4.9%
4 4
 
4.9%
, 4
 
4.9%
Other values (5) 8
9.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.6%
0 11
15.3%
2 10
13.9%
3 7
9.7%
5 6
 
8.3%
6 5
 
6.9%
9 5
 
6.9%
8 4
 
5.6%
4 4
 
5.6%
7 3
 
4.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.8%
0 11
14.1%
2 10
12.8%
3 7
9.0%
5 6
 
7.7%
6 5
 
6.4%
9 5
 
6.4%
8 4
 
5.1%
4 4
 
5.1%
, 4
 
5.1%
Other values (2) 5
 
6.4%
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 11
14.1%
2 10
12.8%
3 7
9.0%
5 6
 
7.7%
6 5
 
6.4%
9 5
 
6.4%
8 4
 
5.1%
4 4
 
5.1%
, 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:25.549721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique25 ?
Unique (%)75.8%

Sample

1st row풍암동
2nd row15,119
3rd row35,056
4th row82
5th row23
ValueCountFrequency (%)
0 4
 
12.1%
1 2
 
6.1%
6 2
 
6.1%
23 2
 
6.1%
127 1
 
3.0%
82 1
 
3.0%
181 1
 
3.0%
34,999 1
 
3.0%
15,108 1
 
3.0%
57 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:27:26.295064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
26.4%
5 11
12.6%
0 7
 
8.0%
2 7
 
8.0%
3 6
 
6.9%
9 6
 
6.9%
8 5
 
5.7%
6 5
 
5.7%
4 4
 
4.6%
, 4
 
4.6%
Other values (5) 9
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
88.5%
Other Punctuation 4
 
4.6%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
29.9%
5 11
14.3%
0 7
 
9.1%
2 7
 
9.1%
3 6
 
7.8%
9 6
 
7.8%
8 5
 
6.5%
6 5
 
6.5%
4 4
 
5.2%
7 3
 
3.9%
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 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
27.4%
5 11
13.1%
0 7
 
8.3%
2 7
 
8.3%
3 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
6 5
 
6.0%
4 4
 
4.8%
, 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 23
27.4%
5 11
13.1%
0 7
 
8.3%
2 7
 
8.3%
3 6
 
7.1%
9 6
 
7.1%
8 5
 
6.0%
6 5
 
6.0%
4 4
 
4.8%
, 4
 
4.8%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:27:26.533133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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

Unique17 ?
Unique (%)51.5%

Sample

1st row동천동
2nd row6,371
3rd row15,542
4th row13
5th row9
ValueCountFrequency (%)
0 8
24.2%
27 2
 
6.1%
9 2
 
6.1%
42 2
 
6.1%
5 2
 
6.1%
13 2
 
6.1%
136 1
 
3.0%
6,355 1
 
3.0%
16 1
 
3.0%
67 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:27:27.101755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12
16.4%
0 10
13.7%
1 9
12.3%
2 8
11.0%
6 6
8.2%
3 5
6.8%
4 5
6.8%
7 5
6.8%
9 4
 
5.5%
, 4
 
5.5%
Other values (3) 5
6.8%

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 (%)
5 12
18.8%
0 10
15.6%
1 9
14.1%
2 8
12.5%
6 6
9.4%
3 5
7.8%
4 5
7.8%
7 5
7.8%
9 4
 
6.2%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 (%)
5 12
17.1%
0 10
14.3%
1 9
12.9%
2 8
11.4%
6 6
8.6%
3 5
7.1%
4 5
7.1%
7 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 12
17.1%
0 10
14.3%
1 9
12.9%
2 8
11.4%
6 6
8.6%
3 5
7.1%
4 5
7.1%
7 5
7.1%
9 4
 
5.7%
, 4
 
5.7%
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>2023.11.03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.10 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>134,4051,9112,1306,6872,8763,9024,858<NA>13,81212,25413,0518,7487,9354,4178,2372,6578,90810,53215,1196,371
4<NA>전월말인구수<NA><NA><NA>285,5373,2904,33011,5994,5477,32810,551<NA>29,43924,04722,80815,64819,9119,31219,5525,67919,59827,30035,05615,542
5<NA>전월말거주불명자수<NA><NA><NA>804253141326524<NA>5815110646282320729238213
6<NA>전월말재외국민등록자수<NA><NA><NA>1623170123<NA>1714861512134411239
7<NA>증 가 요 인전 입<NA>2,6322626149706177<NA>3022792362271429418059115196284109
8<NA><NA><NA>남자<NA>1,335141465313546<NA>14614511611581458136549715559
9<NA><NA><NA>여자<NA>1,297121284392631<NA>15613412011261499923619912950
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>57001000<NA>02701110902060
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>-251-6-2-25-13-26-15<NA>-2-27-2-35-21-3-6-12-8-21-11-16
29<NA>인구수증감<NA><NA><NA>-667-23-19-405-53-38<NA>-48-34-52-53-85-16-18-17-48-44-57-27
30<NA>거주불명자수증감<NA><NA><NA>-670-20-110<NA>2-31-7-2-9-1-80-30-60
31<NA>금월말세대수<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
32<NA>금월말인구수<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
33<NA>금월말거주불명자수<NA><NA><NA>737252941316624<NA>601209944192212726237613
34<NA>금월말재외국민등록자수<NA><NA><NA>1663171122<NA>1914861512134611239

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24# duplicates
0<NA>기타<NA><NA>0000000<NA>0000000000002