Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells201
Missing cells (%)23.0%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text22
Categorical1
DateTime1

Dataset

Description2023-09-14
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: 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 07:22:56.076090
Analysis finished2024-02-10 07:22:57.406260
Duration1.33 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
2024-02-10T07:22:57.681627image/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%
2024-02-10T07:22:58.581389image/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
2024-02-10T07:22:59.054411image/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%
2024-02-10T07:22:59.955669image/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
2024-02-10T07:23:00.416456image/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 row2023.06 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%
2023.06 1
7.1%
현재 1
7.1%
2024-02-10T07:23:01.303971image/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%
6 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%
6 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%
6 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:23:01.740256image/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%
2024-02-10T07:23:02.470805image/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
2024-02-10T07:23:02.918466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.4242424
Min length1

Characters and Unicode

Total characters113
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 row134,116
3rd row286,370
4th row814
5th row157
ValueCountFrequency (%)
0 4
 
11.8%
765 2
 
5.9%
2,706 1
 
2.9%
802 1
 
2.9%
286,100 1
 
2.9%
134,185 1
 
2.9%
12 1
 
2.9%
270 1
 
2.9%
69 1
 
2.9%
5 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:23:04.104493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
15.9%
0 11
9.7%
, 10
8.8%
6 9
8.0%
3 9
8.0%
4 9
8.0%
2 9
8.0%
9 9
8.0%
7 8
7.1%
5 8
7.1%
Other values (5) 13
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97
85.8%
Other Punctuation 10
 
8.8%
Space Separator 2
 
1.8%
Dash Punctuation 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
18.6%
0 11
11.3%
6 9
9.3%
3 9
9.3%
4 9
9.3%
2 9
9.3%
9 9
9.3%
7 8
8.2%
5 8
8.2%
8 7
 
7.2%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111
98.2%
Hangul 2
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
16.2%
0 11
9.9%
, 10
9.0%
6 9
8.1%
3 9
8.1%
4 9
8.1%
2 9
8.1%
9 9
8.1%
7 8
7.2%
5 8
7.2%
Other values (3) 11
9.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111
98.2%
Hangul 2
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
16.2%
0 11
9.9%
, 10
9.0%
6 9
8.1%
3 9
8.1%
4 9
8.1%
2 9
8.1%
9 9
8.1%
7 8
7.2%
5 8
7.2%
Other values (3) 11
9.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:04.620348image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row양동
2nd row1,945
3rd row3,357
4th row26
5th row3
ValueCountFrequency (%)
0 7
21.2%
19 2
 
6.1%
2 2
 
6.1%
3 2
 
6.1%
15 2
 
6.1%
9 2
 
6.1%
4 2
 
6.1%
1 1
 
3.0%
30 1
 
3.0%
8 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:23:05.734124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
17.2%
0 9
14.1%
3 8
12.5%
9 6
9.4%
2 6
9.4%
4 6
9.4%
5 5
7.8%
, 4
 
6.2%
- 3
 
4.7%
6 2
 
3.1%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
85.9%
Other Punctuation 4
 
6.2%
Dash Punctuation 3
 
4.7%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
20.0%
0 9
16.4%
3 8
14.5%
9 6
10.9%
2 6
10.9%
4 6
10.9%
5 5
9.1%
6 2
 
3.6%
7 1
 
1.8%
8 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
17.7%
0 9
14.5%
3 8
12.9%
9 6
9.7%
2 6
9.7%
4 6
9.7%
5 5
8.1%
, 4
 
6.5%
- 3
 
4.8%
6 2
 
3.2%
Other values (2) 2
 
3.2%
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 (%)
1 11
17.7%
0 9
14.5%
3 8
12.9%
9 6
9.7%
2 6
9.7%
4 6
9.7%
5 5
8.1%
, 4
 
6.5%
- 3
 
4.8%
6 2
 
3.2%
Other values (2) 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Categorical

Distinct17
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
1
30
<NA>
12
Other values (12)
15 

Length

Max length5
Median length1
Mean length1.9714286
Min length1

Unique

Unique9 ?
Unique (%)25.7%

Sample

1st row<NA>
2nd row<NA>
3rd row양3동
4th row2,137
5th row4,338

Common Values

ValueCountFrequency (%)
0 9
25.7%
1 4
11.4%
30 3
 
8.6%
<NA> 2
 
5.7%
12 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%
2,137 2
 
5.7%
25 1
 
2.9%
5 1
 
2.9%
Other values (7) 7
20.0%

Length

2024-02-10T07:23:06.299298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 9
25.7%
1 4
11.4%
30 3
 
8.6%
na 2
 
5.7%
12 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%
2,137 2
 
5.7%
18 1
 
2.9%
양3동 1
 
2.9%
Other values (7) 7
20.0%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:06.804203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row농성1동
2nd row6,622
3rd row11,538
4th row43
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
44 2
 
6.1%
2 2
 
6.1%
6 2
 
6.1%
67 1
 
3.0%
77 1
 
3.0%
11,542 1
 
3.0%
6,638 1
 
3.0%
4 1
 
3.0%
16 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:23:08.144746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
15.1%
1 11
15.1%
6 10
13.7%
5 7
9.6%
0 6
8.2%
3 6
8.2%
2 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
7 4
 
5.5%
Other values (5) 5
6.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
16.9%
1 11
16.9%
6 10
15.4%
5 7
10.8%
0 6
9.2%
3 6
9.2%
2 5
7.7%
8 4
 
6.2%
7 4
 
6.2%
9 1
 
1.5%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
15.7%
1 11
15.7%
6 10
14.3%
5 7
10.0%
0 6
8.6%
3 6
8.6%
2 5
7.1%
, 4
 
5.7%
8 4
 
5.7%
7 4
 
5.7%
Other values (2) 2
 
2.9%
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 11
15.7%
1 11
15.7%
6 10
14.3%
5 7
10.0%
0 6
8.6%
3 6
8.6%
2 5
7.1%
, 4
 
5.7%
8 4
 
5.7%
7 4
 
5.7%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:08.662069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성2동
2nd row2,871
3rd row4,573
4th row40
5th row0
ValueCountFrequency (%)
0 9
27.3%
18 3
 
9.1%
27 2
 
6.1%
2 2
 
6.1%
26 1
 
3.0%
37 1
 
3.0%
4,571 1
 
3.0%
2,878 1
 
3.0%
4 1
 
3.0%
7 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:23:09.529242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
1 9
13.2%
2 9
13.2%
7 8
11.8%
8 6
8.8%
4 5
7.4%
5 5
7.4%
, 4
 
5.9%
3 3
 
4.4%
6 3
 
4.4%
Other values (4) 5
7.4%

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 11
18.6%
1 9
15.3%
2 9
15.3%
7 8
13.6%
8 6
10.2%
4 5
8.5%
5 5
8.5%
3 3
 
5.1%
6 3
 
5.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.9%
1 9
13.8%
2 9
13.8%
7 8
12.3%
8 6
9.2%
4 5
7.7%
5 5
7.7%
, 4
 
6.2%
3 3
 
4.6%
6 3
 
4.6%
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 11
16.9%
1 9
13.8%
2 9
13.8%
7 8
12.3%
8 6
9.2%
4 5
7.7%
5 5
7.7%
, 4
 
6.2%
3 3
 
4.6%
6 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:23:10.043872image/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

Unique20 ?
Unique (%)58.8%

Sample

1st row출력일자 :
2nd row광천동
3rd row3,983
4th row7,441
5th row62
ValueCountFrequency (%)
0 7
20.0%
12 4
 
11.4%
20 2
 
5.7%
19 2
 
5.7%
18 1
 
2.9%
52 1
 
2.9%
7,427 1
 
2.9%
3,971 1
 
2.9%
1 1
 
2.9%
14 1
 
2.9%
Other values (14) 14
40.0%
2024-02-10T07:23:10.992145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
2 14
17.9%
0 9
11.5%
4 5
 
6.4%
9 4
 
5.1%
7 4
 
5.1%
, 4
 
5.1%
3 4
 
5.1%
6 3
 
3.8%
- 3
 
3.8%
Other values (11) 13
16.7%

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 (%)
1 15
24.2%
2 14
22.6%
0 9
14.5%
4 5
 
8.1%
9 4
 
6.5%
7 4
 
6.5%
3 4
 
6.5%
6 3
 
4.8%
8 2
 
3.2%
5 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 (%)
- 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 (%)
1 15
21.1%
2 14
19.7%
0 9
12.7%
4 5
 
7.0%
9 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
3 4
 
5.6%
6 3
 
4.2%
- 3
 
4.2%
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 (%)
1 15
21.1%
2 14
19.7%
0 9
12.7%
4 5
 
7.0%
9 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
3 4
 
5.6%
6 3
 
4.2%
- 3
 
4.2%
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
2024-02-10T07:23:11.334482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row유덕동
2nd row4,845
3rd row10,576
4th row20
5th row3
ValueCountFrequency (%)
0 7
21.2%
48 2
 
6.1%
3 2
 
6.1%
4 1
 
3.0%
52 1
 
3.0%
10,567 1
 
3.0%
4,840 1
 
3.0%
2 1
 
3.0%
9 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:23:12.489024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.7%
4 10
14.1%
5 8
11.3%
8 6
8.5%
2 6
8.5%
3 5
 
7.0%
1 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
9 3
 
4.2%
Other values (5) 8
11.3%

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 (%)
0 14
23.0%
4 10
16.4%
5 8
13.1%
8 6
9.8%
2 6
9.8%
3 5
 
8.2%
1 4
 
6.6%
7 3
 
4.9%
9 3
 
4.9%
6 2
 
3.3%
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 (%)
0 14
20.6%
4 10
14.7%
5 8
11.8%
8 6
8.8%
2 6
8.8%
3 5
 
7.4%
1 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
9 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.6%
4 10
14.7%
5 8
11.8%
8 6
8.8%
2 6
8.8%
3 5
 
7.4%
1 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
9 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-07-03 00:00:00
Maximum2023-07-03 00:00:00
2024-02-10T07:23:12.826799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:23:13.135796image/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
2024-02-10T07:23:13.561852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row치평동
2nd row13,650
3rd row29,377
4th row57
5th row17
ValueCountFrequency (%)
0 7
21.2%
167 1
 
3.0%
149 1
 
3.0%
55 1
 
3.0%
29,334 1
 
3.0%
13,653 1
 
3.0%
2 1
 
3.0%
43 1
 
3.0%
3 1
 
3.0%
7 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:23:14.435976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.9%
0 11
13.1%
3 11
13.1%
5 8
9.5%
6 7
8.3%
7 6
 
7.1%
2 5
 
6.0%
9 5
 
6.0%
4 5
 
6.0%
, 4
 
4.8%
Other values (5) 7
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.0%
0 11
14.7%
3 11
14.7%
5 8
10.7%
6 7
9.3%
7 6
 
8.0%
2 5
 
6.7%
9 5
 
6.7%
4 5
 
6.7%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.5%
0 11
13.6%
3 11
13.6%
5 8
9.9%
6 7
8.6%
7 6
 
7.4%
2 5
 
6.2%
9 5
 
6.2%
4 5
 
6.2%
, 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 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
18.5%
0 11
13.6%
3 11
13.6%
5 8
9.9%
6 7
8.6%
7 6
 
7.4%
2 5
 
6.2%
9 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:14.830599image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row상무1동
2nd row12,266
3rd row24,177
4th row152
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
282 1
 
3.0%
132 1
 
3.0%
152 1
 
3.0%
150 1
 
3.0%
24,151 1
 
3.0%
12,253 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:23:16.200947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.5%
2 14
16.5%
0 8
 
9.4%
5 7
 
8.2%
9 6
 
7.1%
8 5
 
5.9%
7 4
 
4.7%
3 4
 
4.7%
, 4
 
4.7%
6 4
 
4.7%
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 20
26.7%
2 14
18.7%
0 8
 
10.7%
5 7
 
9.3%
9 6
 
8.0%
8 5
 
6.7%
7 4
 
5.3%
3 4
 
5.3%
6 4
 
5.3%
4 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 20
24.4%
2 14
17.1%
0 8
 
9.8%
5 7
 
8.5%
9 6
 
7.3%
8 5
 
6.1%
7 4
 
4.9%
3 4
 
4.9%
, 4
 
4.9%
6 4
 
4.9%
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 20
24.4%
2 14
17.1%
0 8
 
9.8%
5 7
 
8.5%
9 6
 
7.3%
8 5
 
6.1%
7 4
 
4.9%
3 4
 
4.9%
, 4
 
4.9%
6 4
 
4.9%
Other values (2) 6
 
7.3%
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
2024-02-10T07:23:16.897015image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row상무2동
2nd row12,992
3rd row22,844
4th row104
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
124 1
 
3.0%
22,837 1
 
3.0%
13,022 1
 
3.0%
4 1
 
3.0%
7 1
 
3.0%
30 1
 
3.0%
19 1
 
3.0%
78 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:23:18.570395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.3%
2 13
16.0%
1 12
14.8%
8 6
7.4%
9 6
7.4%
4 6
7.4%
7 6
7.4%
3 5
 
6.2%
, 4
 
4.9%
6 4
 
4.9%
Other values (5) 5
 
6.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.2%
2 13
17.8%
1 12
16.4%
8 6
8.2%
9 6
8.2%
4 6
8.2%
7 6
8.2%
3 5
 
6.8%
6 4
 
5.5%
5 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
17.9%
2 13
16.7%
1 12
15.4%
8 6
7.7%
9 6
7.7%
4 6
7.7%
7 6
7.7%
3 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
17.9%
2 13
16.7%
1 12
15.4%
8 6
7.7%
9 6
7.7%
4 6
7.7%
7 6
7.7%
3 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
Other values (2) 2
 
2.6%
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
2024-02-10T07:23:19.306956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row화정1동
2nd row8,755
3rd row15,734
4th row45
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
5 2
 
6.1%
95 1
 
3.0%
198 1
 
3.0%
15,715 1
 
3.0%
8,756 1
 
3.0%
2 1
 
3.0%
19 1
 
3.0%
4 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:23:20.404825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
19.2%
1 11
15.1%
7 8
11.0%
0 7
9.6%
6 7
9.6%
4 5
 
6.8%
9 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
3 2
 
2.7%
Other values (5) 6
8.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
21.5%
1 11
16.9%
7 8
12.3%
0 7
10.8%
6 7
10.8%
4 5
 
7.7%
9 5
 
7.7%
8 4
 
6.2%
3 2
 
3.1%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
20.0%
1 11
15.7%
7 8
11.4%
0 7
10.0%
6 7
10.0%
4 5
 
7.1%
9 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
3 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
20.0%
1 11
15.7%
7 8
11.4%
0 7
10.0%
6 7
10.0%
4 5
 
7.1%
9 5
 
7.1%
8 4
 
5.7%
, 4
 
5.7%
3 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:20.859458image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row화정2동
2nd row7,924
3rd row19,917
4th row28
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
15 2
 
6.1%
65 1
 
3.0%
158 1
 
3.0%
19,903 1
 
3.0%
7,931 1
 
3.0%
14 1
 
3.0%
7 1
 
3.0%
4 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:23:21.695744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
0 10
13.3%
9 9
12.0%
7 7
9.3%
5 6
8.0%
2 5
6.7%
3 5
6.7%
6 5
6.7%
, 4
 
5.3%
4 4
 
5.3%
Other values (5) 8
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
0 10
15.2%
9 9
13.6%
7 7
10.6%
5 6
9.1%
2 5
7.6%
3 5
7.6%
6 5
7.6%
4 4
 
6.1%
8 3
 
4.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.7%
0 10
13.9%
9 9
12.5%
7 7
9.7%
5 6
8.3%
2 5
6.9%
3 5
6.9%
6 5
6.9%
, 4
 
5.6%
4 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%
9 9
12.5%
7 7
9.7%
5 6
8.3%
2 5
6.9%
3 5
6.9%
6 5
6.9%
, 4
 
5.6%
4 4
 
5.6%
Other values (2) 5
6.9%
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
2024-02-10T07:23:22.035402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row화정3동
2nd row4,461
3rd row9,431
4th row30
5th row11
ValueCountFrequency (%)
0 7
21.2%
28 2
 
6.1%
11 2
 
6.1%
31 2
 
6.1%
47 1
 
3.0%
30 1
 
3.0%
59 1
 
3.0%
4,458 1
 
3.0%
1 1
 
3.0%
33 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:23:23.203430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.5%
1 10
14.1%
0 9
12.7%
4 8
11.3%
2 7
9.9%
8 6
8.5%
9 5
7.0%
, 4
 
5.6%
5 4
 
5.6%
- 2
 
2.8%
Other values (5) 5
7.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.7%
1 10
16.1%
0 9
14.5%
4 8
12.9%
2 7
11.3%
8 6
9.7%
9 5
8.1%
5 4
 
6.5%
6 1
 
1.6%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
16.2%
1 10
14.7%
0 9
13.2%
4 8
11.8%
2 7
10.3%
8 6
8.8%
9 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
- 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
16.2%
1 10
14.7%
0 9
13.2%
4 8
11.8%
2 7
10.3%
8 6
8.8%
9 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
- 2
 
2.9%
Other values (2) 2
 
2.9%
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
2024-02-10T07:23:23.585742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row화정4동
2nd row8,171
3rd row19,445
4th row23
5th row15
ValueCountFrequency (%)
0 7
21.2%
76 2
 
6.1%
79 1
 
3.0%
21 1
 
3.0%
19,477 1
 
3.0%
8,199 1
 
3.0%
2 1
 
3.0%
32 1
 
3.0%
28 1
 
3.0%
14 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:23:24.503165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.5%
4 9
11.7%
0 8
10.4%
7 7
9.1%
9 7
9.1%
5 6
 
7.8%
2 5
 
6.5%
3 5
 
6.5%
6 4
 
5.2%
, 4
 
5.2%
Other values (5) 7
9.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.7%
4 9
13.0%
0 8
11.6%
7 7
10.1%
9 7
10.1%
5 6
 
8.7%
2 5
 
7.2%
3 5
 
7.2%
6 4
 
5.8%
8 3
 
4.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.3%
4 9
12.2%
0 8
10.8%
7 7
9.5%
9 7
9.5%
5 6
 
8.1%
2 5
 
6.8%
3 5
 
6.8%
6 4
 
5.4%
, 4
 
5.4%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
20.3%
4 9
12.2%
0 8
10.8%
7 7
9.5%
9 7
9.5%
5 6
 
8.1%
2 5
 
6.8%
3 5
 
6.8%
6 4
 
5.4%
, 4
 
5.4%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:24.986885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
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

Unique15 ?
Unique (%)45.5%

Sample

1st row서창동
2nd row2,654
3rd row5,682
4th row8
5th row4
ValueCountFrequency (%)
0 8
24.2%
8 3
 
9.1%
4 3
 
9.1%
34 2
 
6.1%
27 2
 
6.1%
1 2
 
6.1%
25 1
 
3.0%
57 1
 
3.0%
2,653 1
 
3.0%
17 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T07:23:26.014075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
15.9%
2 7
11.1%
5 7
11.1%
4 6
9.5%
8 5
7.9%
3 5
7.9%
6 5
7.9%
7 4
 
6.3%
, 4
 
6.3%
1 4
 
6.3%
Other values (5) 6
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
87.3%
Other Punctuation 4
 
6.3%
Other Letter 3
 
4.8%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
18.2%
2 7
12.7%
5 7
12.7%
4 6
10.9%
8 5
9.1%
3 5
9.1%
6 5
9.1%
7 4
 
7.3%
1 4
 
7.3%
9 2
 
3.6%
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 60
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
16.7%
2 7
11.7%
5 7
11.7%
4 6
10.0%
8 5
8.3%
3 5
8.3%
6 5
8.3%
7 4
 
6.7%
, 4
 
6.7%
1 4
 
6.7%
Other values (2) 3
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
16.7%
2 7
11.7%
5 7
11.7%
4 6
10.0%
8 5
8.3%
3 5
8.3%
6 5
8.3%
7 4
 
6.7%
, 4
 
6.7%
1 4
 
6.7%
Other values (2) 3
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:26.426257image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row금호1동
2nd row8,909
3rd row19,730
4th row30
5th row4
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
4 3
 
9.1%
78 1
 
3.0%
158 1
 
3.0%
19,695 1
 
3.0%
8,908 1
 
3.0%
35 1
 
3.0%
15 1
 
3.0%
47 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:23:27.508127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 13
20.0%
1 10
15.4%
9 8
12.3%
3 7
10.8%
4 6
9.2%
8 6
9.2%
7 5
 
7.7%
5 5
 
7.7%
2 3
 
4.6%
6 2
 
3.1%
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 13
18.1%
1 10
13.9%
9 8
11.1%
3 7
9.7%
4 6
8.3%
8 6
8.3%
7 5
 
6.9%
5 5
 
6.9%
, 4
 
5.6%
- 3
 
4.2%
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 (%)
0 13
18.1%
1 10
13.9%
9 8
11.1%
3 7
9.7%
4 6
8.3%
8 6
8.3%
7 5
 
6.9%
5 5
 
6.9%
, 4
 
5.6%
- 3
 
4.2%
Other values (2) 5
 
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:27.874742image/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 row10,500
3rd row27,323
4th row21
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 3
 
9.1%
21 2
 
6.1%
113 1
 
3.0%
27,323 1
 
3.0%
215 1
 
3.0%
10,511 1
 
3.0%
20 1
 
3.0%
5 1
 
3.0%
79 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:23:28.746170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
24.1%
0 15
19.0%
2 10
12.7%
3 7
 
8.9%
9 5
 
6.3%
7 5
 
6.3%
6 4
 
5.1%
, 4
 
5.1%
5 4
 
5.1%
4 1
 
1.3%
Other values (5) 5
 
6.3%

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 19
26.8%
0 15
21.1%
2 10
14.1%
3 7
 
9.9%
9 5
 
7.0%
7 5
 
7.0%
6 4
 
5.6%
5 4
 
5.6%
4 1
 
1.4%
8 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
25.0%
0 15
19.7%
2 10
13.2%
3 7
 
9.2%
9 5
 
6.6%
7 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
5 4
 
5.3%
4 1
 
1.3%
Other values (2) 2
 
2.6%
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 19
25.0%
0 15
19.7%
2 10
13.2%
3 7
 
9.2%
9 5
 
6.6%
7 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
5 4
 
5.3%
4 1
 
1.3%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:29.160341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row풍암동
2nd row15,091
3rd row35,252
4th row80
5th row22
ValueCountFrequency (%)
0 6
 
18.2%
22 2
 
6.1%
15,091 2
 
6.1%
152 1
 
3.0%
307 1
 
3.0%
35,199 1
 
3.0%
2 1
 
3.0%
53 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:23:30.084551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.0%
2 12
14.3%
5 11
13.1%
0 10
11.9%
3 8
9.5%
9 6
 
7.1%
, 4
 
4.8%
4 4
 
4.8%
8 3
 
3.6%
7 3
 
3.6%
Other values (5) 7
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.3%
2 12
16.0%
5 11
14.7%
0 10
13.3%
3 8
10.7%
9 6
 
8.0%
4 4
 
5.3%
8 3
 
4.0%
7 3
 
4.0%
6 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.8%
2 12
14.8%
5 11
13.6%
0 10
12.3%
3 8
9.9%
9 6
 
7.4%
, 4
 
4.9%
4 4
 
4.9%
8 3
 
3.7%
7 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.8%
2 12
14.8%
5 11
13.6%
0 10
12.3%
3 8
9.9%
9 6
 
7.4%
, 4
 
4.9%
4 4
 
4.9%
8 3
 
3.7%
7 3
 
3.7%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:23:30.446843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row동천동
2nd row6,340
3rd row15,635
4th row15
5th row8
ValueCountFrequency (%)
0 8
24.2%
15 2
 
6.1%
8 2
 
6.1%
17 1
 
3.0%
15,635 1
 
3.0%
56 1
 
3.0%
15,611 1
 
3.0%
6,345 1
 
3.0%
24 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:23:31.380083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
1 10
14.3%
5 10
14.3%
4 10
14.3%
6 7
10.0%
3 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
9 3
 
4.3%
2 3
 
4.3%
Other values (4) 5
7.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.1%
1 10
16.1%
5 10
16.1%
4 10
16.1%
6 7
11.3%
3 5
8.1%
8 3
 
4.8%
9 3
 
4.8%
2 3
 
4.8%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
1 10
14.9%
5 10
14.9%
4 10
14.9%
6 7
10.4%
3 5
7.5%
, 4
 
6.0%
8 3
 
4.5%
9 3
 
4.5%
2 3
 
4.5%
Other values (2) 2
 
3.0%
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%
5 10
14.9%
4 10
14.9%
6 7
10.4%
3 5
7.5%
, 4
 
6.0%
8 3
 
4.5%
9 3
 
4.5%
2 3
 
4.5%
Other values (2) 2
 
3.0%
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>2023.07.03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.06 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>134,1161,9452,1376,6222,8713,9834,845<NA>13,65012,26612,9928,7557,9244,4618,1712,6548,90910,50015,0916,340
4<NA>전월말인구수<NA><NA><NA>286,3703,3574,33811,5384,5737,44110,576<NA>29,37724,17722,84415,73419,9179,43119,4455,68219,73027,32335,25215,635
5<NA>전월말거주불명자수<NA><NA><NA>814263043406220<NA>5715210445283023830218015
6<NA>전월말재외국민등록자수<NA><NA><NA>1573160123<NA>1712851511154411228
7<NA>증 가 요 인전 입<NA>2,4833030158544295<NA>259255261176139591946813319125386
8<NA><NA><NA>남자<NA>1,243151285272048<NA>1161471309169289134709412145
9<NA><NA><NA>여자<NA>1,240151873272247<NA>14310813185703110334639713241
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>5202000<NA>000000000010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>69-40167-12-5<NA>3-133017-328-1-11105
29<NA>인구수증감<NA><NA><NA>-270-1614-2-14-9<NA>-43-26-7-19-14-33328-35-20-53-24
30<NA>거주불명자수증감<NA><NA><NA>-12-10-2-4-1-2<NA>-2-142-11-20-10-20
31<NA>금월말세대수<NA><NA><NA>134,1851,9412,1376,6382,8783,9714,840<NA>13,65312,25313,0228,7567,9314,4588,1992,6538,90810,51115,0916,345
32<NA>금월말인구수<NA><NA><NA>286,1003,3414,33911,5424,5717,42710,567<NA>29,33424,15122,83715,71519,9039,39819,4775,69019,69527,30335,19915,611
33<NA>금월말거주불명자수<NA><NA><NA>802253041366118<NA>5515110847273121829217815
34<NA>금월말재외국민등록자수<NA><NA><NA>1543160123<NA>1512851511134411229

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