Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text23
DateTime1

Dataset

Description2022-04-20
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) 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 07:13:51.765914
Analysis finished2024-02-10 07:13:53.158840
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

인구이동보고서(1호)
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T07:13:53.415900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.875
Min length5

Characters and Unicode

Total characters126
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row행정기관 :
2nd row작성기준 :
3rd row시, 군, 구(읍면동)
4th row전월말세대수
5th row전월말인구수
ValueCountFrequency (%)
요 2
 
7.7%
인 2
 
7.7%
2
 
7.7%
금월말거주불명자수 1
 
3.8%
금월말인구수 1
 
3.8%
금월말세대수 1
 
3.8%
거주불명자수증감 1
 
3.8%
인구수증감 1
 
3.8%
세대수증감 1
 
3.8%
소 1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T07:13:54.749096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
수 11
 
8.7%
말 8
 
6.3%
월 8
 
6.3%
인 5
 
4.0%
자 5
 
4.0%
전 4
 
3.2%
감 4
 
3.2%
증 4
 
3.2%
금 4
 
3.2%
Other values (33) 61
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
82.5%
Control 12
 
9.5%
Space Separator 4
 
3.2%
Other Punctuation 4
 
3.2%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
: 2
50.0%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
82.5%
Common 22
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%
Common
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
82.5%
ASCII 22
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
Hangul
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T07:13:55.161006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3636364
Min length2

Characters and Unicode

Total characters26
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)63.6%

Sample

1st row전 입
2nd row복귀
3rd row출생
4th row등록
5th row국외
ValueCountFrequency (%)
국외 2
15.4%
기타 2
15.4%
전 2
15.4%
입 1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
출 1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T07:13:56.224064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
국 2
 
7.7%
기 2
 
7.7%
타 2
 
7.7%
전 2
 
7.7%
외 2
 
7.7%
출 2
 
7.7%
록 1
 
3.8%
말 1
 
3.8%
망 1
 
3.8%
Other values (7) 7
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Control 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T07:13:56.709457image/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 row2022.03 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
서구 1
7.1%
2022.03 1
7.1%
현재 1
7.1%
2024-02-10T07:13:57.603689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
2 3
 
7.3%
계 2
 
4.9%
0 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
3 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

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

Most frequent character per script

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

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:13:58.012887image/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%
2024-02-10T07:13:58.906537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:59.394891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6969697
Min length1

Characters and Unicode

Total characters122
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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row132,949
3rd row290,550
4th row941
5th row142
ValueCountFrequency (%)
0 5
 
14.7%
992 2
 
5.9%
3 2
 
5.9%
2,069 1
 
2.9%
938 1
 
2.9%
289,789 1
 
2.9%
133,049 1
 
2.9%
761 1
 
2.9%
100 1
 
2.9%
187 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T07:14:00.429283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
17.2%
0 15
12.3%
9 14
11.5%
, 14
11.5%
4 11
9.0%
3 11
9.0%
2 10
8.2%
6 6
 
4.9%
5 5
 
4.1%
8 5
 
4.1%
Other values (5) 10
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
83.6%
Other Punctuation 14
 
11.5%
Space Separator 2
 
1.6%
Dash Punctuation 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
20.6%
0 15
14.7%
9 14
13.7%
4 11
10.8%
3 11
10.8%
2 10
9.8%
6 6
 
5.9%
5 5
 
4.9%
8 5
 
4.9%
7 4
 
3.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 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 120
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
17.5%
0 15
12.5%
9 14
11.7%
, 14
11.7%
4 11
9.2%
3 11
9.2%
2 10
8.3%
6 6
 
5.0%
5 5
 
4.2%
8 5
 
4.2%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
17.5%
0 15
12.5%
9 14
11.7%
, 14
11.7%
4 11
9.2%
3 11
9.2%
2 10
8.3%
6 6
 
5.0%
5 5
 
4.2%
8 5
 
4.2%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:00.942390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row양동
2nd row2,093
3rd row3,652
4th row29
5th row3
ValueCountFrequency (%)
0 8
24.2%
29 3
 
9.1%
33 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
17 2
 
6.1%
3,652 1
 
3.0%
11 1
 
3.0%
2,076 1
 
3.0%
10 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:14:01.823568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.7%
3 11
16.7%
1 9
13.6%
2 8
12.1%
9 5
7.6%
7 5
7.6%
, 4
 
6.1%
6 4
 
6.1%
5 3
 
4.5%
- 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Dash Punctuation 2
 
3.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.0%
3 11
19.0%
1 9
15.5%
2 8
13.8%
9 5
8.6%
7 5
8.6%
6 4
 
6.9%
5 3
 
5.2%
8 1
 
1.7%
4 1
 
1.7%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
3 11
17.2%
1 9
14.1%
2 8
12.5%
9 5
7.8%
7 5
7.8%
, 4
 
6.2%
6 4
 
6.2%
5 3
 
4.7%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.2%
3 11
17.2%
1 9
14.1%
2 8
12.5%
9 5
7.8%
7 5
7.8%
, 4
 
6.2%
6 4
 
6.2%
5 3
 
4.7%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:02.184638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters12
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 row양3동
2nd row2,172
3rd row4,562
4th row32
5th row0
ValueCountFrequency (%)
0 9
27.3%
1 3
 
9.1%
14 2
 
6.1%
21 2
 
6.1%
6 2
 
6.1%
4 1
 
3.0%
32 1
 
3.0%
35 1
 
3.0%
4,541 1
 
3.0%
2,171 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:14:03.223260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.2%
0 10
15.2%
2 9
13.6%
3 8
12.1%
4 6
9.1%
5 5
 
7.6%
, 4
 
6.1%
6 3
 
4.5%
7 3
 
4.5%
- 2
 
3.0%
Other values (2) 2
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Dash Punctuation 2
 
3.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
24.1%
0 10
17.2%
2 9
15.5%
3 8
13.8%
4 6
10.3%
5 5
 
8.6%
6 3
 
5.2%
7 3
 
5.2%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.9%
0 10
15.6%
2 9
14.1%
3 8
12.5%
4 6
9.4%
5 5
 
7.8%
, 4
 
6.2%
6 3
 
4.7%
7 3
 
4.7%
- 2
 
3.1%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
21.9%
0 10
15.6%
2 9
14.1%
3 8
12.5%
4 6
9.4%
5 5
 
7.8%
, 4
 
6.2%
6 3
 
4.7%
7 3
 
4.7%
- 2
 
3.1%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:03.619810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row농성1동
2nd row6,245
3rd row11,020
4th row79
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
74 1
 
3.0%
11,219 1
 
3.0%
6,352 1
 
3.0%
1 1
 
3.0%
199 1
 
3.0%
107 1
 
3.0%
9 1
 
3.0%
55 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:14:04.547396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.9%
0 12
15.6%
2 8
10.4%
9 7
9.1%
8 7
9.1%
5 6
7.8%
7 6
7.8%
6 5
 
6.5%
, 4
 
5.2%
4 4
 
5.2%
Other values (4) 5
 
6.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.6%
0 12
17.1%
2 8
11.4%
9 7
10.0%
8 7
10.0%
5 6
8.6%
7 6
8.6%
6 5
 
7.1%
4 4
 
5.7%
3 2
 
2.9%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.6%
0 12
16.2%
2 8
10.8%
9 7
9.5%
8 7
9.5%
5 6
8.1%
7 6
8.1%
6 5
 
6.8%
, 4
 
5.4%
4 4
 
5.4%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.6%
0 12
16.2%
2 8
10.8%
9 7
9.5%
8 7
9.5%
5 6
8.1%
7 6
8.1%
6 5
 
6.8%
, 4
 
5.4%
4 4
 
5.4%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:04.964826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row농성2동
2nd row2,949
3rd row4,869
4th row53
5th row2
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
2 2
 
6.1%
40 2
 
6.1%
20 2
 
6.1%
6 1
 
3.0%
62 1
 
3.0%
2,949 1
 
3.0%
4,839 1
 
3.0%
2,950 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:14:06.332786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.1%
2 12
17.6%
4 8
11.8%
9 6
8.8%
8 5
 
7.4%
1 4
 
5.9%
3 4
 
5.9%
, 4
 
5.9%
5 3
 
4.4%
6 3
 
4.4%
Other values (5) 6
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
2 12
20.0%
4 8
13.3%
9 6
10.0%
8 5
 
8.3%
1 4
 
6.7%
3 4
 
6.7%
5 3
 
5.0%
6 3
 
5.0%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.0%
2 12
18.5%
4 8
12.3%
9 6
9.2%
8 5
 
7.7%
1 4
 
6.2%
3 4
 
6.2%
, 4
 
6.2%
5 3
 
4.6%
6 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.0%
2 12
18.5%
4 8
12.3%
9 6
9.2%
8 5
 
7.7%
1 4
 
6.2%
3 4
 
6.2%
, 4
 
6.2%
5 3
 
4.6%
6 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct23
Distinct (%)67.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:14:06.983103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3529412
Min length1

Characters and Unicode

Total characters80
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

Unique18 ?
Unique (%)52.9%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,205
4th row7,985
5th row79
ValueCountFrequency (%)
0 8
22.9%
22 2
 
5.7%
74 2
 
5.7%
12 2
 
5.7%
41 2
 
5.7%
63 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
137 1
 
2.9%
7,943 1
 
2.9%
Other values (14) 14
40.0%
2024-02-10T07:14:08.835465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.8%
1 10
12.5%
4 10
12.5%
2 9
11.2%
7 7
8.8%
9 7
8.8%
, 4
 
5.0%
5 4
 
5.0%
3 3
 
3.8%
- 3
 
3.8%
Other values (11) 12
15.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
80.0%
Other Letter 7
 
8.8%
Other Punctuation 5
 
6.2%
Dash Punctuation 3
 
3.8%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 10
15.6%
4 10
15.6%
2 9
14.1%
7 7
10.9%
9 7
10.9%
5 4
 
6.2%
3 3
 
4.7%
8 2
 
3.1%
6 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
91.2%
Hangul 7
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.1%
1 10
13.7%
4 10
13.7%
2 9
12.3%
7 7
9.6%
9 7
9.6%
, 4
 
5.5%
5 4
 
5.5%
3 3
 
4.1%
- 3
 
4.1%
Other values (4) 5
6.8%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
91.2%
Hangul 7
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.1%
1 10
13.7%
4 10
13.7%
2 9
12.3%
7 7
9.6%
9 7
9.6%
, 4
 
5.5%
5 4
 
5.5%
3 3
 
4.1%
- 3
 
4.1%
Other values (4) 5
6.8%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:09.805794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row유덕동
2nd row4,888
3rd row10,960
4th row15
5th row4
ValueCountFrequency (%)
0 8
24.2%
15 2
 
6.1%
4 2
 
6.1%
34 1
 
3.0%
10,960 1
 
3.0%
66 1
 
3.0%
4,891 1
 
3.0%
24 1
 
3.0%
3 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:14:11.093557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.7%
4 9
12.5%
1 9
12.5%
9 7
9.7%
3 6
8.3%
2 5
6.9%
6 5
6.9%
8 5
6.9%
5 4
 
5.6%
, 4
 
5.6%
Other values (5) 6
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.8%
4 9
14.1%
1 9
14.1%
9 7
10.9%
3 6
9.4%
2 5
7.8%
6 5
7.8%
8 5
7.8%
5 4
 
6.2%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.4%
4 9
13.0%
1 9
13.0%
9 7
10.1%
3 6
8.7%
2 5
7.2%
6 5
7.2%
8 5
7.2%
5 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.4%
4 9
13.0%
1 9
13.0%
9 7
10.1%
3 6
8.7%
2 5
7.2%
6 5
7.2%
8 5
7.2%
5 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-04-01 00:00:00
Maximum2022-04-01 00:00:00
2024-02-10T07:14:11.558019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:14:11.927103image/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
2024-02-10T07:14:12.297593image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row치평동
2nd row13,654
3rd row30,299
4th row68
5th row11
ValueCountFrequency (%)
0 7
21.2%
252 1
 
3.0%
228 1
 
3.0%
70 1
 
3.0%
30,139 1
 
3.0%
13,626 1
 
3.0%
2 1
 
3.0%
160 1
 
3.0%
28 1
 
3.0%
18 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:14:13.309963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.3%
0 15
17.0%
2 9
10.2%
8 9
10.2%
3 7
8.0%
6 6
 
6.8%
5 6
 
6.8%
9 6
 
6.8%
, 4
 
4.5%
4 3
 
3.4%
Other values (5) 6
 
6.8%

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 17
21.5%
0 15
19.0%
2 9
11.4%
8 9
11.4%
3 7
8.9%
6 6
 
7.6%
5 6
 
7.6%
9 6
 
7.6%
4 3
 
3.8%
7 1
 
1.3%
Other Letter
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.0%
0 15
17.6%
2 9
10.6%
8 9
10.6%
3 7
8.2%
6 6
 
7.1%
5 6
 
7.1%
9 6
 
7.1%
, 4
 
4.7%
4 3
 
3.5%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.0%
0 15
17.6%
2 9
10.6%
8 9
10.6%
3 7
8.2%
6 6
 
7.1%
5 6
 
7.1%
9 6
 
7.1%
, 4
 
4.7%
4 3
 
3.5%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:13.742125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
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 row상무1동
2nd row12,213
3rd row24,763
4th row125
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
12 2
 
6.1%
1 2
 
6.1%
10 2
 
6.1%
15 1
 
3.0%
391 1
 
3.0%
24,775 1
 
3.0%
12,257 1
 
3.0%
2 1
 
3.0%
44 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:14:15.003201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
27.0%
2 16
18.0%
0 13
14.6%
4 7
 
7.9%
7 5
 
5.6%
5 5
 
5.6%
, 4
 
4.5%
9 4
 
4.5%
3 3
 
3.4%
6 3
 
3.4%
Other values (4) 5
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
92.1%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
29.3%
2 16
19.5%
0 13
15.9%
4 7
 
8.5%
7 5
 
6.1%
5 5
 
6.1%
9 4
 
4.9%
3 3
 
3.7%
6 3
 
3.7%
8 2
 
2.4%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
27.9%
2 16
18.6%
0 13
15.1%
4 7
 
8.1%
7 5
 
5.8%
5 5
 
5.8%
, 4
 
4.7%
9 4
 
4.7%
3 3
 
3.5%
6 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
27.9%
2 16
18.6%
0 13
15.1%
4 7
 
8.1%
7 5
 
5.8%
5 5
 
5.8%
, 4
 
4.7%
9 4
 
4.7%
3 3
 
3.5%
6 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:15.353362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row상무2동
2nd row13,144
3rd row23,832
4th row120
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
120 2
 
6.1%
7 1
 
3.0%
189 1
 
3.0%
23,789 1
 
3.0%
13,171 1
 
3.0%
3 1
 
3.0%
43 1
 
3.0%
27 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:14:16.276975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
21.6%
3 12
13.6%
0 10
11.4%
2 10
11.4%
7 8
9.1%
9 6
 
6.8%
4 6
 
6.8%
8 5
 
5.7%
, 4
 
4.5%
5 3
 
3.4%
Other values (4) 5
 
5.7%

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%
3 12
15.2%
0 10
12.7%
2 10
12.7%
7 8
10.1%
9 6
 
7.6%
4 6
 
7.6%
8 5
 
6.3%
5 3
 
3.8%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.4%
3 12
14.1%
0 10
11.8%
2 10
11.8%
7 8
9.4%
9 6
 
7.1%
4 6
 
7.1%
8 5
 
5.9%
, 4
 
4.7%
5 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
22.4%
3 12
14.1%
0 10
11.8%
2 10
11.8%
7 8
9.4%
9 6
 
7.1%
4 6
 
7.1%
8 5
 
5.9%
, 4
 
4.7%
5 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:16.761127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row화정1동
2nd row8,496
3rd row15,493
4th row43
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
9 2
 
6.1%
7 2
 
6.1%
146 1
 
3.0%
138 1
 
3.0%
15,434 1
 
3.0%
8,487 1
 
3.0%
59 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:14:17.773157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
4 10
12.7%
9 9
11.4%
0 8
10.1%
8 8
10.1%
3 6
 
7.6%
7 4
 
5.1%
, 4
 
5.1%
6 4
 
5.1%
5 3
 
3.8%
Other values (5) 7
8.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.9%
4 10
14.3%
9 9
12.9%
0 8
11.4%
8 8
11.4%
3 6
 
8.6%
7 4
 
5.7%
6 4
 
5.7%
5 3
 
4.3%
2 2
 
2.9%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
4 10
13.2%
9 9
11.8%
0 8
10.5%
8 8
10.5%
3 6
 
7.9%
7 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
5 3
 
3.9%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
21.1%
4 10
13.2%
9 9
11.8%
0 8
10.5%
8 8
10.5%
3 6
 
7.9%
7 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
5 3
 
3.9%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:18.274467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row화정2동
2nd row8,005
3rd row20,558
4th row36
5th row17
ValueCountFrequency (%)
0 6
 
18.2%
17 3
 
9.1%
1 2
 
6.1%
142 1
 
3.0%
258 1
 
3.0%
20,488 1
 
3.0%
7,988 1
 
3.0%
70 1
 
3.0%
8 1
 
3.0%
74 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:14:19.100209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
14.8%
1 12
14.8%
8 12
14.8%
7 9
11.1%
5 8
9.9%
2 6
7.4%
6 5
6.2%
, 4
 
4.9%
4 3
 
3.7%
- 3
 
3.7%
Other values (5) 7
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
8 12
16.9%
7 9
12.7%
5 8
11.3%
2 6
8.5%
6 5
7.0%
4 3
 
4.2%
3 2
 
2.8%
9 2
 
2.8%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
15.4%
1 12
15.4%
8 12
15.4%
7 9
11.5%
5 8
10.3%
2 6
7.7%
6 5
6.4%
, 4
 
5.1%
4 3
 
3.8%
- 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
15.4%
1 12
15.4%
8 12
15.4%
7 9
11.5%
5 8
10.3%
2 6
7.7%
6 5
6.4%
, 4
 
5.1%
4 3
 
3.8%
- 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:19.687292image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row화정3동
2nd row4,634
3rd row10,073
4th row32
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 3
 
9.1%
57 2
 
6.1%
1 2
 
6.1%
50 1
 
3.0%
83 1
 
3.0%
10,031 1
 
3.0%
4,631 1
 
3.0%
42 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:14:20.556494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.8%
3 14
18.2%
0 13
16.9%
4 8
10.4%
5 5
 
6.5%
, 4
 
5.2%
6 4
 
5.2%
7 3
 
3.9%
- 3
 
3.9%
2 2
 
2.6%
Other values (5) 5
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.9%
3 14
20.9%
0 13
19.4%
4 8
11.9%
5 5
 
7.5%
6 4
 
6.0%
7 3
 
4.5%
2 2
 
3.0%
9 1
 
1.5%
8 1
 
1.5%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.6%
3 14
18.9%
0 13
17.6%
4 8
10.8%
5 5
 
6.8%
, 4
 
5.4%
6 4
 
5.4%
7 3
 
4.1%
- 3
 
4.1%
2 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
21.6%
3 14
18.9%
0 13
17.6%
4 8
10.8%
5 5
 
6.8%
, 4
 
5.4%
6 4
 
5.4%
7 3
 
4.1%
- 3
 
4.1%
2 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:21.008409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row화정4동
2nd row6,514
3rd row15,417
4th row45
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
104 1
 
3.0%
15,333 1
 
3.0%
6,496 1
 
3.0%
2 1
 
3.0%
84 1
 
3.0%
18 1
 
3.0%
9 1
 
3.0%
72 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:14:21.967762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.4%
4 12
15.4%
0 9
11.5%
2 9
11.5%
3 6
7.7%
6 5
6.4%
8 5
6.4%
, 4
 
5.1%
5 4
 
5.1%
9 4
 
5.1%
Other values (5) 8
10.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.6%
4 12
17.6%
0 9
13.2%
2 9
13.2%
3 6
8.8%
6 5
7.4%
8 5
7.4%
5 4
 
5.9%
9 4
 
5.9%
7 2
 
2.9%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.0%
4 12
16.0%
0 9
12.0%
2 9
12.0%
3 6
8.0%
6 5
6.7%
8 5
6.7%
, 4
 
5.3%
5 4
 
5.3%
9 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.0%
4 12
16.0%
0 9
12.0%
2 9
12.0%
3 6
8.0%
6 5
6.7%
8 5
6.7%
, 4
 
5.3%
5 4
 
5.3%
9 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:22.334580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row서창동
2nd row2,690
3rd row5,776
4th row28
5th row4
ValueCountFrequency (%)
0 8
24.2%
28 3
 
9.1%
1 2
 
6.1%
4 2
 
6.1%
98 1
 
3.0%
47 1
 
3.0%
5,776 1
 
3.0%
2,690 1
 
3.0%
2,689 1
 
3.0%
22 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:14:23.314685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.9%
2 10
16.9%
8 7
11.9%
4 7
11.9%
1 6
10.2%
6 5
8.5%
5 4
 
6.8%
7 4
 
6.8%
9 3
 
5.1%
3 3
 
5.1%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 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 10
15.4%
2 10
15.4%
8 7
10.8%
4 7
10.8%
1 6
9.2%
6 5
7.7%
5 4
 
6.2%
7 4
 
6.2%
, 4
 
6.2%
9 3
 
4.6%
Other values (2) 5
7.7%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.4%
2 10
15.4%
8 7
10.8%
4 7
10.8%
1 6
9.2%
6 5
7.7%
5 4
 
6.2%
7 4
 
6.2%
, 4
 
6.2%
9 3
 
4.6%
Other values (2) 5
7.7%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:23.746578image/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 categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row금호1동
2nd row8,825
3rd row19,954
4th row40
5th row4
ValueCountFrequency (%)
0 8
24.2%
141 2
 
6.1%
40 2
 
6.1%
4 2
 
6.1%
80 2
 
6.1%
8,825 1
 
3.0%
277 1
 
3.0%
8,852 1
 
3.0%
45 1
 
3.0%
27 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:14:24.658423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.7%
1 13
16.7%
4 9
11.5%
8 7
9.0%
9 7
9.0%
7 7
9.0%
2 7
9.0%
5 6
7.7%
, 4
 
5.1%
3 1
 
1.3%
Other values (4) 4
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
91.0%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
18.3%
1 13
18.3%
4 9
12.7%
8 7
9.9%
9 7
9.9%
7 7
9.9%
2 7
9.9%
5 6
8.5%
3 1
 
1.4%
6 1
 
1.4%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.3%
1 13
17.3%
4 9
12.0%
8 7
9.3%
9 7
9.3%
7 7
9.3%
2 7
9.3%
5 6
8.0%
, 4
 
5.3%
3 1
 
1.3%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.3%
1 13
17.3%
4 9
12.0%
8 7
9.3%
9 7
9.3%
7 7
9.3%
2 7
9.3%
5 6
8.0%
, 4
 
5.3%
3 1
 
1.3%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:25.036983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row금호2동
2nd row10,562
3rd row28,452
4th row26
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
26 2
 
6.1%
5 1
 
3.0%
351 1
 
3.0%
10,548 1
 
3.0%
171 1
 
3.0%
14 1
 
3.0%
13 1
 
3.0%
141 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:14:25.974244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.4%
0 13
15.5%
2 9
10.7%
8 9
10.7%
5 7
 
8.3%
7 6
 
7.1%
4 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
3 4
 
4.8%
Other values (4) 5
 
6.0%

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 18
24.0%
0 13
17.3%
2 9
12.0%
8 9
12.0%
5 7
 
9.3%
7 6
 
8.0%
4 5
 
6.7%
6 4
 
5.3%
3 4
 
5.3%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.2%
0 13
16.0%
2 9
11.1%
8 9
11.1%
5 7
 
8.6%
7 6
 
7.4%
4 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
3 4
 
4.9%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.2%
0 13
16.0%
2 9
11.1%
8 9
11.1%
5 7
 
8.6%
7 6
 
7.4%
4 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
3 4
 
4.9%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:26.395546image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row풍암동
2nd row15,270
3rd row36,692
4th row81
5th row22
ValueCountFrequency (%)
0 6
 
18.2%
22 2
 
6.1%
243 1
 
3.0%
263 1
 
3.0%
36,529 1
 
3.0%
15,278 1
 
3.0%
3 1
 
3.0%
163 1
 
3.0%
8 1
 
3.0%
1 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:14:27.348277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
17.4%
1 11
12.8%
3 10
11.6%
0 9
10.5%
6 8
9.3%
8 7
8.1%
5 6
 
7.0%
7 5
 
5.8%
, 4
 
4.7%
9 4
 
4.7%
Other values (5) 7
8.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
19.5%
1 11
14.3%
3 10
13.0%
0 9
11.7%
6 8
10.4%
8 7
9.1%
5 6
 
7.8%
7 5
 
6.5%
9 4
 
5.2%
4 2
 
2.6%
Other Letter
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
18.1%
1 11
13.3%
3 10
12.0%
0 9
10.8%
6 8
9.6%
8 7
8.4%
5 6
 
7.2%
7 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
18.1%
1 11
13.3%
3 10
12.0%
0 9
10.8%
6 8
9.6%
8 7
8.4%
5 6
 
7.2%
7 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:14:27.742804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row동천동
2nd row6,390
3rd row16,193
4th row10
5th row3
ValueCountFrequency (%)
0 8
24.2%
32 2
 
6.1%
10 2
 
6.1%
3 2
 
6.1%
6 2
 
6.1%
71 1
 
3.0%
107 1
 
3.0%
6,395 1
 
3.0%
53 1
 
3.0%
5 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:14:28.752093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
23.9%
3 10
14.1%
1 10
14.1%
6 8
11.3%
5 6
 
8.5%
9 5
 
7.0%
, 4
 
5.6%
7 3
 
4.2%
2 2
 
2.8%
4 2
 
2.8%
Other values (3) 4
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
27.0%
3 10
15.9%
1 10
15.9%
6 8
12.7%
5 6
 
9.5%
9 5
 
7.9%
7 3
 
4.8%
2 2
 
3.2%
4 2
 
3.2%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
25.0%
3 10
14.7%
1 10
14.7%
6 8
11.8%
5 6
 
8.8%
9 5
 
7.4%
, 4
 
5.9%
7 3
 
4.4%
2 2
 
2.9%
4 2
 
2.9%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
25.0%
3 10
14.7%
1 10
14.7%
6 8
11.8%
5 6
 
8.8%
9 5
 
7.4%
, 4
 
5.9%
7 3
 
4.4%
2 2
 
2.9%
4 2
 
2.9%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24
0<NA>행정기관 :<NA>광주광역시 서구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.04.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.03 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>132,9492,0932,1726,2452,9494,2054,888<NA>13,65412,21313,1448,4968,0054,6346,5142,6908,82510,56215,2706,390
4<NA>전월말인구수<NA><NA><NA>290,5503,6524,56211,0204,8697,98510,960<NA>30,29924,76323,83215,49320,55810,07315,4175,77619,95428,45236,69216,193
5<NA>전월말거주불명자수<NA><NA><NA>941293279537915<NA>68125120433632452840268110
6<NA>전월말재외국민등록자수<NA><NA><NA>1423052124<NA>111097171111447223
7<NA>증 가 요 인전 입계<NA>3,415293536262100112<NA>31940034523018511412381277187347107
8<NA><NA><NA>남자<NA>1,7331121178345962<NA>1682041701118857614114110316856
9<NA><NA><NA>여자<NA>1,6821814184284150<NA>151196175119975762401368417951
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>3000000<NA>010100000010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>100-17-11071-143<NA>-284427-9-17-3-18-127-1485
29<NA>인구수증감<NA><NA><NA>-761-33-21199-30-42-24<NA>-16012-43-59-70-42-84-2245-171-163-53
30<NA>거주불명자수증감<NA><NA><NA>-30111-10<NA>22-31-1-1-2000-30
31<NA>금월말세대수<NA><NA><NA>133,0492,0762,1716,3522,9504,1914,891<NA>13,62612,25713,1718,4877,9884,6316,4962,6898,85210,54815,2786,395
32<NA>금월말인구수<NA><NA><NA>289,7893,6194,54111,2194,8397,94310,936<NA>30,13924,77523,78915,43420,48810,03115,3335,75419,99928,28136,52916,140
33<NA>금월말거주불명자수<NA><NA><NA>938293380547815<NA>70127117443531432840267810
34<NA>금월말재외국민등록자수<NA><NA><NA>1413052124<NA>101097171111447223

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
1<NA>기타<NA><NA>0000000<NA>0000000000002