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

Description2023-02-23
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 07:19:31.530639
Analysis finished2024-02-10 07:19:33.215028
Duration1.68 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
2024-02-10T07:19:33.814156image/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%
2024-02-10T07:19:34.743374image/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
2024-02-10T07:19:35.158566image/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%
2024-02-10T07:19:35.945637image/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
2024-02-10T07:19:36.448726image/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 row2023.01 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%
2023.01 1
7.1%
현재 1
7.1%
2024-02-10T07:19:37.311101image/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
2024-02-10T07:19:37.720090image/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%
2024-02-10T07:19:38.452777image/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
2024-02-10T07:19:38.826630image/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 row133,554
3rd row287,401
4th row956
5th row147
ValueCountFrequency (%)
0 4
 
11.8%
780 2
 
5.9%
2,902 1
 
2.9%
883 1
 
2.9%
287,347 1
 
2.9%
133,676 1
 
2.9%
73 1
 
2.9%
54 1
 
2.9%
122 1
 
2.9%
7 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:19:39.780220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
16.7%
, 13
10.8%
4 13
10.8%
2 12
10.0%
0 11
9.2%
7 10
8.3%
8 9
7.5%
3 8
 
6.7%
5 7
 
5.8%
6 6
 
5.0%
Other values (5) 11
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
84.2%
Other Punctuation 13
 
10.8%
Space Separator 2
 
1.7%
Dash Punctuation 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
19.8%
4 13
12.9%
2 12
11.9%
0 11
10.9%
7 10
9.9%
8 9
8.9%
3 8
 
7.9%
5 7
 
6.9%
6 6
 
5.9%
9 5
 
5.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
16.9%
, 13
11.0%
4 13
11.0%
2 12
10.2%
0 11
9.3%
7 10
8.5%
8 9
7.6%
3 8
 
6.8%
5 7
 
5.9%
6 6
 
5.1%
Other values (3) 9
7.6%
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 20
16.9%
, 13
11.0%
4 13
11.0%
2 12
10.2%
0 11
9.3%
7 10
8.5%
8 9
7.6%
3 8
 
6.8%
5 7
 
5.9%
6 6
 
5.1%
Other values (3) 9
7.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:40.155256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8484848
Min length1

Characters and Unicode

Total characters61
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

Unique14 ?
Unique (%)42.4%

Sample

1st row양동
2nd row1,976
3rd row3,425
4th row29
5th row3
ValueCountFrequency (%)
0 8
24.2%
12 3
 
9.1%
3 3
 
9.1%
4 3
 
9.1%
11 2
 
6.1%
23 1
 
3.0%
19 1
 
3.0%
29 1
 
3.0%
7 1
 
3.0%
3,425 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T07:19:41.073135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
18.0%
0 9
14.8%
2 8
13.1%
3 6
9.8%
4 5
8.2%
9 5
8.2%
, 4
 
6.6%
7 3
 
4.9%
8 2
 
3.3%
6 2
 
3.3%
Other values (4) 6
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
86.9%
Other Punctuation 4
 
6.6%
Dash Punctuation 2
 
3.3%
Other Letter 2
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
20.8%
0 9
17.0%
2 8
15.1%
3 6
11.3%
4 5
9.4%
9 5
9.4%
7 3
 
5.7%
8 2
 
3.8%
6 2
 
3.8%
5 2
 
3.8%
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 59
96.7%
Hangul 2
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
18.6%
0 9
15.3%
2 8
13.6%
3 6
10.2%
4 5
8.5%
9 5
8.5%
, 4
 
6.8%
7 3
 
5.1%
8 2
 
3.4%
6 2
 
3.4%
Other values (2) 4
 
6.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
96.7%
Hangul 2
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
18.6%
0 9
15.3%
2 8
13.6%
3 6
10.2%
4 5
8.5%
9 5
8.5%
, 4
 
6.8%
7 3
 
5.1%
8 2
 
3.4%
6 2
 
3.4%
Other values (2) 4
 
6.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:41.374194image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row양3동
2nd row2,152
3rd row4,433
4th row32
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 4
 
12.1%
22 2
 
6.1%
양3동 1
 
3.0%
23 1
 
3.0%
4,411 1
 
3.0%
2,147 1
 
3.0%
5 1
 
3.0%
4 1
 
3.0%
12 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:19:42.241777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.2%
2 12
18.2%
0 9
13.6%
4 7
10.6%
3 7
10.6%
, 4
 
6.1%
- 3
 
4.5%
5 2
 
3.0%
6 2
 
3.0%
7 2
 
3.0%
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 14
24.6%
2 12
21.1%
0 9
15.8%
4 7
12.3%
3 7
12.3%
5 2
 
3.5%
6 2
 
3.5%
7 2
 
3.5%
8 1
 
1.8%
9 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 14
21.9%
2 12
18.8%
0 9
14.1%
4 7
10.9%
3 7
10.9%
, 4
 
6.2%
- 3
 
4.7%
5 2
 
3.1%
6 2
 
3.1%
7 2
 
3.1%
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 14
21.9%
2 12
18.8%
0 9
14.1%
4 7
10.9%
3 7
10.9%
, 4
 
6.2%
- 3
 
4.7%
5 2
 
3.1%
6 2
 
3.1%
7 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:42.584375image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row농성1동
2nd row6,409
3rd row11,243
4th row41
5th row5
ValueCountFrequency (%)
0 6
18.2%
5 3
 
9.1%
78 2
 
6.1%
59 2
 
6.1%
41 2
 
6.1%
1 1
 
3.0%
148 1
 
3.0%
11,321 1
 
3.0%
6,463 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:19:43.421219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
0 10
13.3%
4 8
10.7%
5 7
9.3%
9 6
8.0%
2 6
8.0%
3 6
8.0%
7 4
 
5.3%
8 4
 
5.3%
6 4
 
5.3%
Other values (5) 8
10.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.9%
0 10
14.9%
4 8
11.9%
5 7
10.4%
9 6
9.0%
2 6
9.0%
3 6
9.0%
7 4
 
6.0%
8 4
 
6.0%
6 4
 
6.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.7%
0 10
13.9%
4 8
11.1%
5 7
9.7%
9 6
8.3%
2 6
8.3%
3 6
8.3%
7 4
 
5.6%
8 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
6.9%
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 (%)
1 12
16.7%
0 10
13.9%
4 8
11.1%
5 7
9.7%
9 6
8.3%
2 6
8.3%
3 6
8.3%
7 4
 
5.6%
8 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:43.854359image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row농성2동
2nd row2,902
3rd row4,689
4th row49
5th row0
ValueCountFrequency (%)
0 9
27.3%
26 2
 
6.1%
22 2
 
6.1%
13 2
 
6.1%
1 2
 
6.1%
48 2
 
6.1%
76 1
 
3.0%
23 1
 
3.0%
2,890 1
 
3.0%
33 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:19:44.725582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
19.7%
0 11
15.5%
4 7
9.9%
6 7
9.9%
3 6
8.5%
1 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
- 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
23.0%
0 11
18.0%
4 7
11.5%
6 7
11.5%
3 6
9.8%
1 5
 
8.2%
8 4
 
6.6%
9 4
 
6.6%
7 2
 
3.3%
5 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
20.6%
0 11
16.2%
4 7
10.3%
6 7
10.3%
3 6
8.8%
1 5
 
7.4%
8 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
20.6%
0 11
16.2%
4 7
10.3%
6 7
10.3%
3 6
8.8%
1 5
 
7.4%
8 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct27
Distinct (%)79.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:19:45.099154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
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 row4,063
4th row7,636
5th row70
ValueCountFrequency (%)
0 5
 
14.3%
3 3
 
8.6%
26 2
 
5.7%
1 2
 
5.7%
출력일자 1
 
2.9%
67 1
 
2.9%
7,610 1
 
2.9%
4,037 1
 
2.9%
30 1
 
2.9%
33 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T07:19:45.980237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
16.7%
0 10
12.8%
1 8
10.3%
6 8
10.3%
7 8
10.3%
2 7
9.0%
, 4
 
5.1%
4 3
 
3.8%
- 3
 
3.8%
8 2
 
2.6%
Other values (11) 12
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
79.5%
Other Letter 7
 
9.0%
Other Punctuation 5
 
6.4%
Dash Punctuation 3
 
3.8%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 13
21.0%
0 10
16.1%
1 8
12.9%
6 8
12.9%
7 8
12.9%
2 7
11.3%
4 3
 
4.8%
8 2
 
3.2%
9 2
 
3.2%
5 1
 
1.6%
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 (%)
- 3
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 (%)
3 13
18.3%
0 10
14.1%
1 8
11.3%
6 8
11.3%
7 8
11.3%
2 7
9.9%
, 4
 
5.6%
4 3
 
4.2%
- 3
 
4.2%
8 2
 
2.8%
Other values (4) 5
 
7.0%
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 (%)
3 13
18.3%
0 10
14.1%
1 8
11.3%
6 8
11.3%
7 8
11.3%
2 7
9.9%
, 4
 
5.6%
4 3
 
4.2%
- 3
 
4.2%
8 2
 
2.8%
Other values (4) 5
 
7.0%
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 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:46.313532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row유덕동
2nd row4,859
3rd row10,684
4th row32
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
86 2
 
6.1%
5 2
 
6.1%
10,684 2
 
6.1%
22 1
 
3.0%
46 1
 
3.0%
4,869 1
 
3.0%
9 1
 
3.0%
10 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:19:47.140520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.4%
3 9
13.0%
4 8
11.6%
1 6
8.7%
6 6
8.7%
8 6
8.7%
5 5
7.2%
2 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.7%
3 9
14.8%
4 8
13.1%
1 6
9.8%
6 6
9.8%
8 6
9.8%
5 5
8.2%
2 5
8.2%
9 4
 
6.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
3 9
13.6%
4 8
12.1%
1 6
9.1%
6 6
9.1%
8 6
9.1%
5 5
7.6%
2 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.2%
3 9
13.6%
4 8
12.1%
1 6
9.1%
6 6
9.1%
8 6
9.1%
5 5
7.6%
2 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
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
Minimum2023-02-01 00:00:00
Maximum2023-02-01 00:00:00
2024-02-10T07:19:47.492795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:19:47.901932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:48.256715image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row치평동
2nd row13,518
3rd row29,433
4th row67
5th row16
ValueCountFrequency (%)
0 5
 
15.2%
141 2
 
6.1%
16 2
 
6.1%
2 1
 
3.0%
339 1
 
3.0%
29,414 1
 
3.0%
13,538 1
 
3.0%
4 1
 
3.0%
19 1
 
3.0%
20 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:19:49.171319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
25.3%
3 10
11.5%
2 9
10.3%
4 8
 
9.2%
0 6
 
6.9%
6 6
 
6.9%
9 5
 
5.7%
7 5
 
5.7%
, 4
 
4.6%
8 4
 
4.6%
Other values (5) 8
 
9.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
28.2%
3 10
12.8%
2 9
11.5%
4 8
 
10.3%
0 6
 
7.7%
6 6
 
7.7%
9 5
 
6.4%
7 5
 
6.4%
8 4
 
5.1%
5 3
 
3.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
26.2%
3 10
11.9%
2 9
10.7%
4 8
 
9.5%
0 6
 
7.1%
6 6
 
7.1%
9 5
 
6.0%
7 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
Other values (2) 5
 
6.0%
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 22
26.2%
3 10
11.9%
2 9
10.7%
4 8
 
9.5%
0 6
 
7.1%
6 6
 
7.1%
9 5
 
6.0%
7 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:49.718528image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row상무1동
2nd row12,218
3rd row24,353
4th row196
5th row10
ValueCountFrequency (%)
0 7
21.2%
107 2
 
6.1%
10 2
 
6.1%
12 1
 
3.0%
311 1
 
3.0%
24,323 1
 
3.0%
12,220 1
 
3.0%
15 1
 
3.0%
30 1
 
3.0%
2 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:19:51.439886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
25.8%
0 14
15.7%
2 12
13.5%
3 7
 
7.9%
7 6
 
6.7%
5 6
 
6.7%
, 4
 
4.5%
9 4
 
4.5%
8 3
 
3.4%
4 3
 
3.4%
Other values (5) 7
 
7.9%

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 23
28.7%
0 14
17.5%
2 12
15.0%
3 7
 
8.8%
7 6
 
7.5%
5 6
 
7.5%
9 4
 
5.0%
8 3
 
3.8%
4 3
 
3.8%
6 2
 
2.5%
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 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
26.7%
0 14
16.3%
2 12
14.0%
3 7
 
8.1%
7 6
 
7.0%
5 6
 
7.0%
, 4
 
4.7%
9 4
 
4.7%
8 3
 
3.5%
4 3
 
3.5%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
26.7%
0 14
16.3%
2 12
14.0%
3 7
 
8.1%
7 6
 
7.0%
5 6
 
7.0%
, 4
 
4.7%
9 4
 
4.7%
8 3
 
3.5%
4 3
 
3.5%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:51.956876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5757576
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row상무2동
2nd row12,984
3rd row23,028
4th row120
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
3 2
 
6.1%
159 1
 
3.0%
23,006 1
 
3.0%
12,981 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
11 1
 
3.0%
118 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:19:53.468271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
16.5%
2 13
15.3%
0 11
12.9%
9 8
9.4%
8 8
9.4%
3 6
7.1%
4 6
7.1%
, 4
 
4.7%
7 3
 
3.5%
5 3
 
3.5%
Other values (5) 9
10.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.7%
2 13
17.3%
0 11
14.7%
9 8
10.7%
8 8
10.7%
3 6
8.0%
4 6
8.0%
7 3
 
4.0%
5 3
 
4.0%
6 3
 
4.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.1%
2 13
15.9%
0 11
13.4%
9 8
9.8%
8 8
9.8%
3 6
7.3%
4 6
7.3%
, 4
 
4.9%
7 3
 
3.7%
5 3
 
3.7%
Other values (2) 6
7.3%
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 14
17.1%
2 13
15.9%
0 11
13.4%
9 8
9.8%
8 8
9.8%
3 6
7.3%
4 6
7.3%
, 4
 
4.9%
7 3
 
3.7%
5 3
 
3.7%
Other values (2) 6
7.3%
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
2024-02-10T07:19:54.012088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row화정1동
2nd row8,523
3rd row15,465
4th row47
5th row6
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
6 2
 
6.1%
90 1
 
3.0%
95 1
 
3.0%
15,522 1
 
3.0%
8,568 1
 
3.0%
57 1
 
3.0%
45 1
 
3.0%
7 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:19:54.931779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
18.4%
1 11
14.5%
0 9
11.8%
8 7
9.2%
6 6
7.9%
2 5
 
6.6%
4 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
3 3
 
3.9%
Other values (5) 7
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
89.5%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
20.6%
1 11
16.2%
0 9
13.2%
8 7
10.3%
6 6
8.8%
2 5
 
7.4%
4 5
 
7.4%
7 5
 
7.4%
3 3
 
4.4%
9 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
19.2%
1 11
15.1%
0 9
12.3%
8 7
9.6%
6 6
8.2%
2 5
 
6.8%
4 5
 
6.8%
7 5
 
6.8%
, 4
 
5.5%
3 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
19.2%
1 11
15.1%
0 9
12.3%
8 7
9.6%
6 6
8.2%
2 5
 
6.8%
4 5
 
6.8%
7 5
 
6.8%
, 4
 
5.5%
3 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:55.512146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row화정2동
2nd row7,883
3rd row19,933
4th row31
5th row16
ValueCountFrequency (%)
0 7
21.2%
7,883 2
 
6.1%
16 2
 
6.1%
71 2
 
6.1%
1 2
 
6.1%
108 1
 
3.0%
31 1
 
3.0%
217 1
 
3.0%
19,943 1
 
3.0%
10 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:19:56.403491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
0 12
15.2%
3 10
12.7%
9 8
10.1%
7 7
8.9%
8 5
 
6.3%
2 5
 
6.3%
, 4
 
5.1%
6 3
 
3.8%
5 3
 
3.8%
Other values (5) 6
 
7.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.5%
0 12
16.9%
3 10
14.1%
9 8
11.3%
7 7
9.9%
8 5
 
7.0%
2 5
 
7.0%
6 3
 
4.2%
5 3
 
4.2%
4 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
0 12
15.8%
3 10
13.2%
9 8
10.5%
7 7
9.2%
8 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
6 3
 
3.9%
5 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
21.1%
0 12
15.8%
3 10
13.2%
9 8
10.5%
7 7
9.2%
8 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
6 3
 
3.9%
5 3
 
3.9%
Other values (2) 3
 
3.9%
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
2024-02-10T07:19:57.005295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row화정3동
2nd row4,509
3rd row9,595
4th row40
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
27 2
 
6.1%
34 2
 
6.1%
48 2
 
6.1%
44 1
 
3.0%
4,500 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
4 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:19:57.880281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
4 10
13.9%
1 8
11.1%
9 7
9.7%
5 7
9.7%
3 7
9.7%
6 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
2 3
 
4.2%
Other values (5) 8
11.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
4 10
16.1%
1 8
12.9%
9 7
11.3%
5 7
11.3%
3 7
11.3%
6 4
 
6.5%
8 3
 
4.8%
2 3
 
4.8%
7 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
4 10
14.5%
1 8
11.6%
9 7
10.1%
5 7
10.1%
3 7
10.1%
6 4
 
5.8%
, 4
 
5.8%
8 3
 
4.3%
2 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
4 10
14.5%
1 8
11.6%
9 7
10.1%
5 7
10.1%
3 7
10.1%
6 4
 
5.8%
, 4
 
5.8%
8 3
 
4.3%
2 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:19:58.398620image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row화정4동
2nd row7,956
3rd row18,858
4th row26
5th row15
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
72 1
 
3.0%
19,018 1
 
3.0%
8,014 1
 
3.0%
2 1
 
3.0%
160 1
 
3.0%
58 1
 
3.0%
16 1
 
3.0%
81 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:19:59.730246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.8%
0 11
13.6%
5 8
9.9%
7 7
8.6%
8 7
8.6%
4 7
8.6%
6 5
 
6.2%
, 4
 
4.9%
9 4
 
4.9%
2 4
 
4.9%
Other values (5) 8
9.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.9%
0 11
15.1%
5 8
11.0%
7 7
9.6%
8 7
9.6%
4 7
9.6%
6 5
 
6.8%
9 4
 
5.5%
2 4
 
5.5%
3 4
 
5.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.5%
0 11
14.1%
5 8
10.3%
7 7
9.0%
8 7
9.0%
4 7
9.0%
6 5
 
6.4%
, 4
 
5.1%
9 4
 
5.1%
2 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 16
20.5%
0 11
14.1%
5 8
10.3%
7 7
9.0%
8 7
9.0%
4 7
9.0%
6 5
 
6.4%
, 4
 
5.1%
9 4
 
5.1%
2 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:20:00.132948image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row서창동
2nd row2,668
3rd row5,692
4th row12
5th row4
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
1 2
 
6.1%
4 2
 
6.1%
27 1
 
3.0%
25 1
 
3.0%
5,691 1
 
3.0%
2,659 1
 
3.0%
2 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:20:01.044060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
17.9%
1 10
14.9%
0 9
13.4%
5 6
9.0%
9 6
9.0%
6 5
7.5%
, 4
 
6.0%
3 4
 
6.0%
4 3
 
4.5%
- 3
 
4.5%
Other values (5) 5
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
85.1%
Other Punctuation 4
 
6.0%
Dash Punctuation 3
 
4.5%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
21.1%
1 10
17.5%
0 9
15.8%
5 6
10.5%
9 6
10.5%
6 5
8.8%
3 4
 
7.0%
4 3
 
5.3%
8 1
 
1.8%
7 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
18.8%
1 10
15.6%
0 9
14.1%
5 6
9.4%
9 6
9.4%
6 5
7.8%
, 4
 
6.2%
3 4
 
6.2%
4 3
 
4.7%
- 3
 
4.7%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
18.8%
1 10
15.6%
0 9
14.1%
5 6
9.4%
9 6
9.4%
6 5
7.8%
, 4
 
6.2%
3 4
 
6.2%
4 3
 
4.7%
- 3
 
4.7%
Other values (2) 2
 
3.1%
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
2024-02-10T07:20:01.576891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row금호1동
2nd row8,972
3rd row19,982
4th row40
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
45 2
 
6.1%
4 2
 
6.1%
46 1
 
3.0%
85 1
 
3.0%
19,957 1
 
3.0%
8,969 1
 
3.0%
5 1
 
3.0%
25 1
 
3.0%
3 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:20:02.513549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
13.6%
5 9
13.6%
1 9
13.6%
0 8
12.1%
6 8
12.1%
9 7
10.6%
2 6
9.1%
8 4
6.1%
3 4
6.1%
7 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
12.3%
5 9
12.3%
1 9
12.3%
0 8
11.0%
6 8
11.0%
9 7
9.6%
2 6
8.2%
8 4
5.5%
, 4
5.5%
3 4
5.5%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9
12.3%
5 9
12.3%
1 9
12.3%
0 8
11.0%
6 8
11.0%
9 7
9.6%
2 6
8.2%
8 4
5.5%
, 4
5.5%
3 4
5.5%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:20:02.885783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.3939394
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row금호2동
2nd row10,464
3rd row27,531
4th row25
5th row7
ValueCountFrequency (%)
0 6
18.2%
63 2
 
6.1%
3 2
 
6.1%
51 2
 
6.1%
7 2
 
6.1%
112 1
 
3.0%
219 1
 
3.0%
27,480 1
 
3.0%
10,467 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:20:03.649821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
0 12
15.2%
2 8
10.1%
7 7
8.9%
6 6
 
7.6%
5 6
 
7.6%
4 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
9 2
 
2.5%
Other values (5) 7
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
88.6%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.9%
0 12
17.1%
2 8
11.4%
7 7
10.0%
6 6
 
8.6%
5 6
 
8.6%
4 6
 
8.6%
3 5
 
7.1%
9 2
 
2.9%
8 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
0 12
15.8%
2 8
10.5%
7 7
9.2%
6 6
 
7.9%
5 6
 
7.9%
4 6
 
7.9%
3 5
 
6.6%
, 4
 
5.3%
9 2
 
2.6%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
21.1%
0 12
15.8%
2 8
10.5%
7 7
9.2%
6 6
 
7.9%
5 6
 
7.9%
4 6
 
7.9%
3 5
 
6.6%
, 4
 
5.3%
9 2
 
2.6%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:20:04.220000image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row풍암동
2nd row15,134
3rd row35,593
4th row81
5th row22
ValueCountFrequency (%)
0 5
 
15.2%
124 2
 
6.1%
78 2
 
6.1%
22 2
 
6.1%
316 1
 
3.0%
156 1
 
3.0%
35,515 1
 
3.0%
15,124 1
 
3.0%
4 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:20:05.101560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.8%
2 11
12.9%
5 11
12.9%
0 9
10.6%
4 7
8.2%
3 6
 
7.1%
8 5
 
5.9%
7 5
 
5.9%
6 4
 
4.7%
, 4
 
4.7%
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 16
21.1%
2 11
14.5%
5 11
14.5%
0 9
11.8%
4 7
9.2%
3 6
 
7.9%
8 5
 
6.6%
7 5
 
6.6%
6 4
 
5.3%
9 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 16
19.5%
2 11
13.4%
5 11
13.4%
0 9
11.0%
4 7
8.5%
3 6
 
7.3%
8 5
 
6.1%
7 5
 
6.1%
6 4
 
4.9%
, 4
 
4.9%
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 16
19.5%
2 11
13.4%
5 11
13.4%
0 9
11.0%
4 7
8.5%
3 6
 
7.3%
8 5
 
6.1%
7 5
 
6.1%
6 4
 
4.9%
, 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:20:05.466096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row동천동
2nd row6,364
3rd row15,828
4th row18
5th row5
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
5 2
 
6.1%
52 1
 
3.0%
18 1
 
3.0%
15,828 1
 
3.0%
15,819 1
 
3.0%
6,367 1
 
3.0%
1 1
 
3.0%
9 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:20:06.331299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
1 10
14.3%
3 9
12.9%
6 7
10.0%
8 7
10.0%
5 5
7.1%
4 5
7.1%
, 4
 
5.7%
9 3
 
4.3%
7 3
 
4.3%
Other values (4) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.4%
1 10
16.4%
3 9
14.8%
6 7
11.5%
8 7
11.5%
5 5
8.2%
4 5
8.2%
9 3
 
4.9%
7 3
 
4.9%
2 2
 
3.3%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
1 10
14.9%
3 9
13.4%
6 7
10.4%
8 7
10.4%
5 5
7.5%
4 5
7.5%
, 4
 
6.0%
9 3
 
4.5%
7 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.9%
1 10
14.9%
3 9
13.4%
6 7
10.4%
8 7
10.4%
5 5
7.5%
4 5
7.5%
, 4
 
6.0%
9 3
 
4.5%
7 3
 
4.5%
Other values (2) 4
 
6.0%
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>2023.02.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.01 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계양동양3동농성1동농성2동광천동유덕동<NA>치평동상무1동상무2동화정1동화정2동화정3동화정4동서창동금호1동금호2동풍암동동천동
3<NA>전월말세대수<NA><NA><NA>133,5541,9762,1526,4092,9024,0634,859<NA>13,51812,21812,9848,5237,8834,5097,9562,6688,97210,46415,1346,364
4<NA>전월말인구수<NA><NA><NA>287,4013,4254,43311,2434,6897,63610,684<NA>29,43324,35323,02815,46519,9339,59518,8585,69219,98227,53135,59315,828
5<NA>전월말거주불명자수<NA><NA><NA>956293241497032<NA>67196120473140261240258118
6<NA>전월말재외국민등록자수<NA><NA><NA>1473150123<NA>161076161115447225
7<NA>증 가 요 인전 입<NA>2,9131926223485886<NA>321278289248234653345312617124886
8<NA><NA><NA>남자<NA>1,4561210100262751<NA>1491411451351292715929629012440
9<NA><NA><NA>여자<NA>1,457716123223135<NA>1721371441131053817524648112446
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>7010000<NA>003000000030
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>1224-554-12-2610<NA>202-3450-958-9-33-103
29<NA>인구수증감<NA><NA><NA>-54-9-2278-33-260<NA>-19-30-225710-34160-1-25-51-78-9
30<NA>거주불명자수증감<NA><NA><NA>-73-2-1-2-1-3-9<NA>-4-15-21-1-1-6-2-2-5-14-1
31<NA>금월말세대수<NA><NA><NA>133,6761,9802,1476,4632,8904,0374,869<NA>13,53812,22012,9818,5687,8834,5008,0142,6598,96910,46715,1246,367
32<NA>금월말인구수<NA><NA><NA>287,3473,4164,41111,3214,6567,61010,684<NA>29,41424,32323,00615,52219,9439,56119,0185,69119,95727,48035,51515,819
33<NA>금월말거주불명자수<NA><NA><NA>883273139486723<NA>6318199463034241035248517
34<NA>금월말재외국민등록자수<NA><NA><NA>1483150133<NA>161076161115447225

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