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

Description2023-04-14
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: 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 07:20:53.264562
Analysis finished2024-02-10 07:20:54.691948
Duration1.43 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
2024-02-10T07:20:54.930364image/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%
2024-02-10T07:20:56.057625image/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
2024-02-10T07:20:56.574513image/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%
2024-02-10T07:20:57.552925image/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
2024-02-10T07:20:58.318409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
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 row2023.03 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%
2023.03 1
7.1%
현재 1
7.1%
2024-02-10T07:21:00.210780image/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%
0 2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 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 (%)
0 2
33.3%
3 2
33.3%
2 2
33.3%
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%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 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%
0 2
20.0%
3 2
20.0%
2 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:21:00.659904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T07:21:02.630196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:03.092022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6666667
Min length1

Characters and Unicode

Total characters121
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 row133,857
3rd row287,237
4th row848
5th row151
ValueCountFrequency (%)
0 4
 
11.8%
864 2
 
5.9%
1,746 1
 
2.9%
837 1
 
2.9%
286,826 1
 
2.9%
133,935 1
 
2.9%
11 1
 
2.9%
411 1
 
2.9%
78 1
 
2.9%
1 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:21:04.008878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
18.2%
8 14
11.6%
, 14
11.6%
3 13
10.7%
4 12
9.9%
5 9
7.4%
0 8
 
6.6%
6 7
 
5.8%
2 7
 
5.8%
7 6
 
5.0%
Other values (5) 9
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
83.5%
Other Punctuation 14
 
11.6%
Space Separator 2
 
1.7%
Dash Punctuation 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
21.8%
8 14
13.9%
3 13
12.9%
4 12
11.9%
5 9
8.9%
0 8
 
7.9%
6 7
 
6.9%
2 7
 
6.9%
7 6
 
5.9%
9 3
 
3.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119
98.3%
Hangul 2
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
18.5%
8 14
11.8%
, 14
11.8%
3 13
10.9%
4 12
10.1%
5 9
7.6%
0 8
 
6.7%
6 7
 
5.9%
2 7
 
5.9%
7 6
 
5.0%
Other values (3) 7
 
5.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119
98.3%
Hangul 2
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
18.5%
8 14
11.8%
, 14
11.8%
3 13
10.9%
4 12
10.1%
5 9
7.6%
0 8
 
6.7%
6 7
 
5.9%
2 7
 
5.9%
7 6
 
5.0%
Other values (3) 7
 
5.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:04.423037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row양동
2nd row1,977
3rd row3,408
4th row27
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
27 2
 
6.1%
16 2
 
6.1%
5 2
 
6.1%
7 1
 
3.0%
3,408 1
 
3.0%
26 1
 
3.0%
1,972 1
 
3.0%
12 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:21:05.406928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
15.9%
1 10
15.9%
3 7
11.1%
7 7
11.1%
2 5
7.9%
6 5
7.9%
, 4
 
6.3%
9 4
 
6.3%
8 3
 
4.8%
4 2
 
3.2%
Other values (4) 6
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
87.3%
Other Punctuation 4
 
6.3%
Dash Punctuation 2
 
3.2%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
18.2%
1 10
18.2%
3 7
12.7%
7 7
12.7%
2 5
9.1%
6 5
9.1%
9 4
 
7.3%
8 3
 
5.5%
4 2
 
3.6%
5 2
 
3.6%
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 61
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
16.4%
1 10
16.4%
3 7
11.5%
7 7
11.5%
2 5
8.2%
6 5
8.2%
, 4
 
6.6%
9 4
 
6.6%
8 3
 
4.9%
4 2
 
3.3%
Other values (2) 4
 
6.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
16.4%
1 10
16.4%
3 7
11.5%
7 7
11.5%
2 5
8.2%
6 5
8.2%
, 4
 
6.6%
9 4
 
6.6%
8 3
 
4.9%
4 2
 
3.3%
Other values (2) 4
 
6.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:05.811321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row양3동
2nd row2,139
3rd row4,389
4th row30
5th row1
ValueCountFrequency (%)
0 8
24.2%
21 3
 
9.1%
1 3
 
9.1%
10 2
 
6.1%
16 2
 
6.1%
30 2
 
6.1%
25 1
 
3.0%
36 1
 
3.0%
20 1
 
3.0%
4,389 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T07:21:06.837488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
22.4%
0 13
19.4%
2 9
13.4%
3 8
11.9%
6 4
 
6.0%
, 4
 
6.0%
4 3
 
4.5%
5 3
 
4.5%
8 3
 
4.5%
9 2
 
3.0%
Other values (3) 3
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
89.6%
Other Punctuation 4
 
6.0%
Other Letter 2
 
3.0%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
25.0%
0 13
21.7%
2 9
15.0%
3 8
13.3%
6 4
 
6.7%
4 3
 
5.0%
5 3
 
5.0%
8 3
 
5.0%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
23.1%
0 13
20.0%
2 9
13.8%
3 8
12.3%
6 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
5 3
 
4.6%
8 3
 
4.6%
9 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
23.1%
0 13
20.0%
2 9
13.8%
3 8
12.3%
6 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
5 3
 
4.6%
8 3
 
4.6%
9 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:07.188971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row농성1동
2nd row6,535
3rd row11,402
4th row40
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
75 1
 
3.0%
42 1
 
3.0%
11,411 1
 
3.0%
6,556 1
 
3.0%
2 1
 
3.0%
9 1
 
3.0%
21 1
 
3.0%
64 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:08.218412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.7%
0 10
13.9%
6 10
13.9%
5 9
12.5%
4 6
8.3%
2 6
8.3%
3 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
8 3
 
4.2%
Other values (4) 5
6.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.5%
0 10
15.4%
6 10
15.4%
5 9
13.8%
4 6
9.2%
2 6
9.2%
3 4
 
6.2%
9 3
 
4.6%
8 3
 
4.6%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.4%
0 10
14.5%
6 10
14.5%
5 9
13.0%
4 6
8.7%
2 6
8.7%
3 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
8 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.4%
0 10
14.5%
6 10
14.5%
5 9
13.0%
4 6
8.7%
2 6
8.7%
3 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
8 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:08.700280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row농성2동
2nd row2,888
3rd row4,632
4th row47
5th row0
ValueCountFrequency (%)
0 10
30.3%
29 2
 
6.1%
33 1
 
3.0%
49 1
 
3.0%
4,592 1
 
3.0%
2,867 1
 
3.0%
2 1
 
3.0%
40 1
 
3.0%
21 1
 
3.0%
4 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:21:09.676627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
23.3%
0 11
18.3%
4 8
13.3%
8 5
 
8.3%
7 5
 
8.3%
9 4
 
6.7%
3 4
 
6.7%
1 4
 
6.7%
6 3
 
5.0%
5 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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
20.9%
0 11
16.4%
4 8
11.9%
8 5
 
7.5%
7 5
 
7.5%
9 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
1 4
 
6.0%
6 3
 
4.5%
Other values (2) 5
 
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
20.9%
0 11
16.4%
4 8
11.9%
8 5
 
7.5%
7 5
 
7.5%
9 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
1 4
 
6.0%
6 3
 
4.5%
Other values (2) 5
 
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:21:10.096725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3235294
Min length1

Characters and Unicode

Total characters79
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,019
4th row7,561
5th row65
ValueCountFrequency (%)
0 8
22.9%
13 2
 
5.7%
24 2
 
5.7%
55 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
48 1
 
2.9%
7,511 1
 
2.9%
3,997 1
 
2.9%
2 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T07:21:11.082092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.9%
1 10
12.7%
2 8
10.1%
4 6
 
7.6%
3 6
 
7.6%
5 6
 
7.6%
6 5
 
6.3%
8 4
 
5.1%
7 4
 
5.1%
, 4
 
5.1%
Other values (11) 15
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
79.7%
Other Letter 7
 
8.9%
Other Punctuation 5
 
6.3%
Dash Punctuation 3
 
3.8%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.5%
1 10
15.9%
2 8
12.7%
4 6
9.5%
3 6
9.5%
5 6
9.5%
6 5
7.9%
8 4
 
6.3%
7 4
 
6.3%
9 3
 
4.8%
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 72
91.1%
Hangul 7
 
8.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
1 10
13.9%
2 8
11.1%
4 6
8.3%
3 6
8.3%
5 6
8.3%
6 5
6.9%
8 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
Other values (4) 8
11.1%
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 72
91.1%
Hangul 7
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.3%
1 10
13.9%
2 8
11.1%
4 6
8.3%
3 6
8.3%
5 6
8.3%
6 5
6.9%
8 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
Other values (4) 8
11.1%
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
2024-02-10T07:21:11.567833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row유덕동
2nd row4,858
3rd row10,634
4th row21
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
1 2
 
6.1%
56 1
 
3.0%
10,606 1
 
3.0%
4,859 1
 
3.0%
28 1
 
3.0%
8 1
 
3.0%
44 1
 
3.0%
39 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:21:12.431199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
3 8
11.3%
1 8
11.3%
8 7
9.9%
5 7
9.9%
4 6
8.5%
6 6
8.5%
2 5
7.0%
, 4
 
5.6%
9 3
 
4.2%
Other values (4) 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 (%)
0 12
19.4%
3 8
12.9%
1 8
12.9%
8 7
11.3%
5 7
11.3%
4 6
9.7%
6 6
9.7%
2 5
8.1%
9 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
3 8
11.8%
1 8
11.8%
8 7
10.3%
5 7
10.3%
4 6
8.8%
6 6
8.8%
2 5
7.4%
, 4
 
5.9%
9 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 (%)
0 12
17.6%
3 8
11.8%
1 8
11.8%
8 7
10.3%
5 7
10.3%
4 6
8.8%
6 6
8.8%
2 5
7.4%
, 4
 
5.9%
9 3
 
4.4%
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
Minimum2023-04-03 00:00:00
Maximum2023-04-03 00:00:00
2024-02-10T07:21:12.967348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:21:13.323216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:13.662611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row치평동
2nd row13,577
3rd row29,433
4th row59
5th row16
ValueCountFrequency (%)
0 5
 
15.2%
57 2
 
6.1%
2 2
 
6.1%
16 2
 
6.1%
182 1
 
3.0%
354 1
 
3.0%
13,594 1
 
3.0%
44 1
 
3.0%
17 1
 
3.0%
1 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:14.514587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.1%
3 10
11.6%
9 8
9.3%
7 7
 
8.1%
4 7
 
8.1%
0 6
 
7.0%
5 6
 
7.0%
2 6
 
7.0%
6 4
 
4.7%
, 4
 
4.7%
Other values (5) 9
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
24.7%
3 10
13.0%
9 8
10.4%
7 7
 
9.1%
4 7
 
9.1%
0 6
 
7.8%
5 6
 
7.8%
2 6
 
7.8%
6 4
 
5.2%
8 4
 
5.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.9%
3 10
12.0%
9 8
9.6%
7 7
 
8.4%
4 7
 
8.4%
0 6
 
7.2%
5 6
 
7.2%
2 6
 
7.2%
6 4
 
4.8%
, 4
 
4.8%
Other values (2) 6
 
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
22.9%
3 10
12.0%
9 8
9.6%
7 7
 
8.4%
4 7
 
8.4%
0 6
 
7.2%
5 6
 
7.2%
2 6
 
7.2%
6 4
 
4.8%
, 4
 
4.8%
Other values (2) 6
 
7.2%
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
2024-02-10T07:21:14.912091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row상무1동
2nd row12,222
3rd row24,249
4th row170
5th row10
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
10 2
 
6.1%
140 1
 
3.0%
173 1
 
3.0%
24,226 1
 
3.0%
12,243 1
 
3.0%
23 1
 
3.0%
21 1
 
3.0%
18 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:21:16.154280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
21.6%
2 16
18.2%
0 13
14.8%
3 10
11.4%
4 5
 
5.7%
8 5
 
5.7%
, 4
 
4.5%
7 4
 
4.5%
6 3
 
3.4%
9 2
 
2.3%
Other values (5) 7
 
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
24.1%
2 16
20.3%
0 13
16.5%
3 10
12.7%
4 5
 
6.3%
8 5
 
6.3%
7 4
 
5.1%
6 3
 
3.8%
9 2
 
2.5%
5 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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.4%
2 16
18.8%
0 13
15.3%
3 10
11.8%
4 5
 
5.9%
8 5
 
5.9%
, 4
 
4.7%
7 4
 
4.7%
6 3
 
3.5%
9 2
 
2.4%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
22.4%
2 16
18.8%
0 13
15.3%
3 10
11.8%
4 5
 
5.9%
8 5
 
5.9%
, 4
 
4.7%
7 4
 
4.7%
6 3
 
3.5%
9 2
 
2.4%
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
2024-02-10T07:21:16.566262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row상무2동
2nd row12,947
3rd row22,928
4th row99
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
8 2
 
6.1%
158 1
 
3.0%
307 1
 
3.0%
22,951 1
 
3.0%
12,980 1
 
3.0%
4 1
 
3.0%
23 1
 
3.0%
33 1
 
3.0%
5 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:21:17.400740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
16.9%
2 13
15.7%
0 12
14.5%
9 9
10.8%
8 8
9.6%
3 6
7.2%
, 4
 
4.8%
4 4
 
4.8%
7 4
 
4.8%
5 4
 
4.8%
Other values (4) 5
 
6.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.4%
2 13
17.1%
0 12
15.8%
9 9
11.8%
8 8
10.5%
3 6
7.9%
4 4
 
5.3%
7 4
 
5.3%
5 4
 
5.3%
6 2
 
2.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.5%
2 13
16.2%
0 12
15.0%
9 9
11.2%
8 8
10.0%
3 6
7.5%
, 4
 
5.0%
4 4
 
5.0%
7 4
 
5.0%
5 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.5%
2 13
16.2%
0 12
15.0%
9 9
11.2%
8 8
10.0%
3 6
7.5%
, 4
 
5.0%
4 4
 
5.0%
7 4
 
5.0%
5 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:17.886255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row화정1동
2nd row8,656
3rd row15,655
4th row44
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
6 2
 
6.1%
129 1
 
3.0%
44 1
 
3.0%
15,655 1
 
3.0%
15,664 1
 
3.0%
8,695 1
 
3.0%
9 1
 
3.0%
39 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:21:18.660419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
6 11
14.7%
0 7
9.3%
2 7
9.3%
5 7
9.3%
4 6
8.0%
8 6
8.0%
9 6
8.0%
7 4
 
5.3%
, 4
 
5.3%
Other values (4) 5
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
90.7%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.6%
6 11
16.2%
0 7
10.3%
2 7
10.3%
5 7
10.3%
4 6
8.8%
8 6
8.8%
9 6
8.8%
7 4
 
5.9%
3 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
6 11
15.3%
0 7
9.7%
2 7
9.7%
5 7
9.7%
4 6
8.3%
8 6
8.3%
9 6
8.3%
7 4
 
5.6%
, 4
 
5.6%
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%
6 11
15.3%
0 7
9.7%
2 7
9.7%
5 7
9.7%
4 6
8.3%
8 6
8.3%
9 6
8.3%
7 4
 
5.6%
, 4
 
5.6%
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
2024-02-10T07:21:19.022434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
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

Unique20 ?
Unique (%)60.6%

Sample

1st row화정2동
2nd row7,902
3rd row19,968
4th row30
5th row16
ValueCountFrequency (%)
0 7
21.2%
16 2
 
6.1%
30 2
 
6.1%
6 2
 
6.1%
110 1
 
3.0%
19,968 1
 
3.0%
213 1
 
3.0%
7,909 1
 
3.0%
27 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:21:19.804842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.9%
1 12
15.4%
9 9
11.5%
6 8
10.3%
2 8
10.3%
7 8
10.3%
3 5
 
6.4%
8 5
 
6.4%
, 4
 
5.1%
1
 
1.3%
Other values (4) 4
 
5.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.0%
1 12
17.1%
9 9
12.9%
6 8
11.4%
2 8
11.4%
7 8
11.4%
3 5
 
7.1%
8 5
 
7.1%
4 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.7%
1 12
16.0%
9 9
12.0%
6 8
10.7%
2 8
10.7%
7 8
10.7%
3 5
 
6.7%
8 5
 
6.7%
, 4
 
5.3%
- 1
 
1.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
18.7%
1 12
16.0%
9 9
12.0%
6 8
10.7%
2 8
10.7%
7 8
10.7%
3 5
 
6.7%
8 5
 
6.7%
, 4
 
5.3%
- 1
 
1.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:20.268627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
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 row화정3동
2nd row4,490
3rd row9,508
4th row33
5th row11
ValueCountFrequency (%)
0 6
18.2%
24 3
 
9.1%
1 2
 
6.1%
49 2
 
6.1%
11 2
 
6.1%
118 1
 
3.0%
9,459 1
 
3.0%
4,466 1
 
3.0%
4 1
 
3.0%
48 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:21:21.206213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 14
18.9%
0 9
12.2%
1 9
12.2%
2 8
10.8%
9 8
10.8%
, 4
 
5.4%
8 4
 
5.4%
3 4
 
5.4%
6 4
 
5.4%
- 3
 
4.1%
Other values (5) 7
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 14
21.9%
0 9
14.1%
1 9
14.1%
2 8
12.5%
9 8
12.5%
8 4
 
6.2%
3 4
 
6.2%
6 4
 
6.2%
5 2
 
3.1%
7 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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14
19.7%
0 9
12.7%
1 9
12.7%
2 8
11.3%
9 8
11.3%
, 4
 
5.6%
8 4
 
5.6%
3 4
 
5.6%
6 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 14
19.7%
0 9
12.7%
1 9
12.7%
2 8
11.3%
9 8
11.3%
, 4
 
5.6%
8 4
 
5.6%
3 4
 
5.6%
6 4
 
5.6%
- 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:21.569788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row화정4동
2nd row8,083
3rd row19,189
4th row22
5th row15
ValueCountFrequency (%)
0 7
21.2%
16 2
 
6.1%
71 2
 
6.1%
125 1
 
3.0%
22 1
 
3.0%
15 1
 
3.0%
19,319 1
 
3.0%
8,121 1
 
3.0%
1 1
 
3.0%
130 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:21:22.503844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
24.4%
0 10
12.2%
2 10
12.2%
9 9
11.0%
3 7
 
8.5%
8 6
 
7.3%
6 4
 
4.9%
, 4
 
4.9%
7 3
 
3.7%
5 3
 
3.7%
Other values (4) 6
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
91.5%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
26.7%
0 10
13.3%
2 10
13.3%
9 9
12.0%
3 7
 
9.3%
8 6
 
8.0%
6 4
 
5.3%
7 3
 
4.0%
5 3
 
4.0%
4 3
 
4.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
25.3%
0 10
12.7%
2 10
12.7%
9 9
11.4%
3 7
 
8.9%
8 6
 
7.6%
6 4
 
5.1%
, 4
 
5.1%
7 3
 
3.8%
5 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
25.3%
0 10
12.7%
2 10
12.7%
9 9
11.4%
3 7
 
8.9%
8 6
 
7.6%
6 4
 
5.1%
, 4
 
5.1%
7 3
 
3.8%
5 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:22.857943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row서창동
2nd row2,651
3rd row5,675
4th row9
5th row4
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
9 2
 
6.1%
4 2
 
6.1%
1 2
 
6.1%
50 1
 
3.0%
33 1
 
3.0%
2,669 1
 
3.0%
13 1
 
3.0%
18 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:21:23.853253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
16.9%
0 9
13.8%
5 7
10.8%
6 6
9.2%
3 6
9.2%
4 5
7.7%
2 5
7.7%
, 4
 
6.2%
8 4
 
6.2%
9 3
 
4.6%
Other values (4) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
19.0%
0 9
15.5%
5 7
12.1%
6 6
10.3%
3 6
10.3%
4 5
8.6%
2 5
8.6%
8 4
 
6.9%
9 3
 
5.2%
7 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
17.7%
0 9
14.5%
5 7
11.3%
6 6
9.7%
3 6
9.7%
4 5
8.1%
2 5
8.1%
, 4
 
6.5%
8 4
 
6.5%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
17.7%
0 9
14.5%
5 7
11.3%
6 6
9.7%
3 6
9.7%
4 5
8.1%
2 5
8.1%
, 4
 
6.5%
8 4
 
6.5%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:24.346952image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row금호1동
2nd row8,963
3rd row19,922
4th row36
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 3
 
9.1%
36 2
 
6.1%
34 2
 
6.1%
63 1
 
3.0%
88 1
 
3.0%
8,938 1
 
3.0%
2 1
 
3.0%
66 1
 
3.0%
25 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:21:25.389489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 9
13.8%
3 9
13.8%
6 9
13.8%
4 7
10.8%
8 7
10.8%
9 7
10.8%
1 6
9.2%
2 5
7.7%
5 5
7.7%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

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

Unnamed: 22
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:21:25.749756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
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 row금호2동
2nd row10,477
3rd row27,437
4th row24
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
152 1
 
3.0%
27,364 1
 
3.0%
10,482 1
 
3.0%
3 1
 
3.0%
73 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
119 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:26.728874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.1%
1 12
14.6%
2 11
13.4%
4 7
8.5%
7 7
8.5%
6 6
7.3%
3 5
 
6.1%
, 4
 
4.9%
5 4
 
4.9%
8 4
 
4.9%
Other values (5) 8
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
89.0%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.2%
1 12
16.4%
2 11
15.1%
4 7
9.6%
7 7
9.6%
6 6
8.2%
3 5
 
6.8%
5 4
 
5.5%
8 4
 
5.5%
9 3
 
4.1%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
17.7%
1 12
15.2%
2 11
13.9%
4 7
8.9%
7 7
8.9%
6 6
7.6%
3 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
8 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
17.7%
1 12
15.2%
2 11
13.9%
4 7
8.9%
7 7
8.9%
6 6
7.6%
3 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
8 4
 
5.1%
Other values (2) 5
 
6.3%
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
2024-02-10T07:21:27.110296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row풍암동
2nd row15,112
3rd row35,462
4th row75
5th row22
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
22 2
 
6.1%
198 1
 
3.0%
188 1
 
3.0%
35,357 1
 
3.0%
15,094 1
 
3.0%
105 1
 
3.0%
18 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:21:27.896923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.8%
5 11
12.8%
2 9
10.5%
8 9
10.5%
0 8
9.3%
4 6
 
7.0%
3 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
7 4
 
4.7%
Other values (5) 9
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
22.1%
5 11
14.3%
2 9
11.7%
8 9
11.7%
0 8
10.4%
4 6
 
7.8%
3 5
 
6.5%
6 4
 
5.2%
7 4
 
5.2%
9 4
 
5.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.5%
5 11
13.3%
2 9
10.8%
8 9
10.8%
0 8
9.6%
4 6
 
7.2%
3 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
7 4
 
4.8%
Other values (2) 6
 
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.5%
5 11
13.3%
2 9
10.8%
8 9
10.8%
0 8
9.6%
4 6
 
7.2%
3 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
7 4
 
4.8%
Other values (2) 6
 
7.2%
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
2024-02-10T07:21:28.388253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters14
Distinct 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 row동천동
2nd row6,361
3rd row15,785
4th row17
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
79 1
 
3.0%
15,785 1
 
3.0%
92 1
 
3.0%
6,352 1
 
3.0%
57 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:21:29.261893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
14.1%
0 9
12.7%
4 9
12.7%
5 8
11.3%
7 7
9.9%
6 6
8.5%
2 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
3 3
 
4.2%
Other values (4) 8
11.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
16.1%
0 9
14.5%
4 9
14.5%
5 8
12.9%
7 7
11.3%
6 6
9.7%
2 4
 
6.5%
8 3
 
4.8%
3 3
 
4.8%
9 3
 
4.8%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
14.7%
0 9
13.2%
4 9
13.2%
5 8
11.8%
7 7
10.3%
6 6
8.8%
2 4
 
5.9%
, 4
 
5.9%
8 3
 
4.4%
3 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
14.7%
0 9
13.2%
4 9
13.2%
5 8
11.8%
7 7
10.3%
6 6
8.8%
2 4
 
5.9%
, 4
 
5.9%
8 3
 
4.4%
3 3
 
4.4%
Other values (2) 5
7.4%
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>2023.04.03<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.03 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>133,8571,9772,1396,5352,8884,0194,858<NA>13,57712,22212,9478,6567,9024,4908,0832,6518,96310,47715,1126,361
4<NA>전월말인구수<NA><NA><NA>287,2373,4084,38911,4024,6327,56110,634<NA>29,43324,24922,92815,65519,9689,50819,1895,67519,92227,43735,46215,785
5<NA>전월말거주불명자수<NA><NA><NA>848273040476521<NA>591709944303322936247517
6<NA>전월말재외국민등록자수<NA><NA><NA>1513150133<NA>1610761611154410225
7<NA>증 가 요 인전 입<NA>3,0222636165466886<NA>311301326262213703526412020028492
8<NA><NA><NA>남자<NA>1,534162072294451<NA>14316217412010642162346410414942
9<NA><NA><NA>여자<NA>1,488101693172435<NA>1681391521421072819030569613550
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>5000000<NA>100120000010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>1000000<NA>000000000010
28<NA>세대수증감<NA><NA><NA>78-5221-21-221<NA>172133397-243818-255-18-9
29<NA>인구수증감<NA><NA><NA>-411-12-219-40-50-28<NA>-44-23239-27-4913013-66-73-105-57
30<NA>거주불명자수증감<NA><NA><NA>-11002-2-2-1<NA>-2-7410-110-2-310
31<NA>금월말세대수<NA><NA><NA>133,9351,9722,1416,5562,8673,9974,859<NA>13,59412,24312,9808,6957,9094,4668,1212,6698,93810,48215,0946,352
32<NA>금월말인구수<NA><NA><NA>286,8263,3964,36811,4114,5927,51110,606<NA>29,38924,22622,95115,66419,9419,45919,3195,68819,85627,36435,35715,728
33<NA>금월말거주불명자수<NA><NA><NA>837273042456320<NA>5716310345303223934217617
34<NA>금월말재외국민등록자수<NA><NA><NA>1543160133<NA>1610861611164410225

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>국외<NA><NA>0000000<NA>0000000000002