Overview

Dataset statistics

Number of variables21
Number of observations46
Missing cells377
Missing cells (%)39.0%
Duplicate rows2
Duplicate rows (%)4.3%
Total size in memory7.7 KiB
Average record size in memory170.9 B

Variable types

Categorical3
Text18

Dataset

Description장애인유형별,등급별등록현황201512월기준_20160425
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201724

Alerts

Dataset has 2 (4.3%) duplicate rowsDuplicates
장애인 유형별, 등급별 등록 현황 is highly imbalanced (53.8%)Imbalance
Unnamed: 1 has 12 (26.1%) missing valuesMissing
Unnamed: 2 has 12 (26.1%) missing valuesMissing
Unnamed: 3 has 11 (23.9%) missing valuesMissing
Unnamed: 4 has 12 (26.1%) missing valuesMissing
Unnamed: 5 has 12 (26.1%) missing valuesMissing
Unnamed: 6 has 11 (23.9%) missing valuesMissing
Unnamed: 7 has 12 (26.1%) missing valuesMissing
Unnamed: 8 has 11 (23.9%) missing valuesMissing
Unnamed: 9 has 28 (60.9%) missing valuesMissing
Unnamed: 10 has 29 (63.0%) missing valuesMissing
Unnamed: 11 has 29 (63.0%) missing valuesMissing
Unnamed: 12 has 28 (60.9%) missing valuesMissing
Unnamed: 13 has 29 (63.0%) missing valuesMissing
Unnamed: 14 has 29 (63.0%) missing valuesMissing
Unnamed: 15 has 28 (60.9%) missing valuesMissing
Unnamed: 16 has 29 (63.0%) missing valuesMissing
Unnamed: 17 has 29 (63.0%) missing valuesMissing
Unnamed: 18 has 26 (56.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 01:00:01.640167
Analysis finished2024-03-14 01:00:02.045424
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장애인 유형별, 등급별 등록 현황
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
37 
전라북도
4 
(2015년 12월)
 
2
구분
 
2
장애인 유형별, 등급별 등록 현황
 
1

Length

Max length18
Median length4
Mean length4.5217391
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row(2015년 12월)
2nd row<NA>
3rd row<NA>
4th row전라북도
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 37
80.4%
전라북도 4
 
8.7%
(2015년 12월) 2
 
4.3%
구분 2
 
4.3%
장애인 유형별, 등급별 등록 현황 1
 
2.2%

Length

2024-03-14T10:00:02.103960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:00:02.188527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
71.2%
전라북도 4
 
7.7%
2015년 2
 
3.8%
12월 2
 
3.8%
구분 2
 
3.8%
장애인 1
 
1.9%
유형별 1
 
1.9%
등급별 1
 
1.9%
등록 1
 
1.9%
현황 1
 
1.9%

Unnamed: 1
Text

MISSING 

Distinct17
Distinct (%)50.0%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-03-14T10:00:02.331600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4705882
Min length1

Characters and Unicode

Total characters84
Distinct characters34
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

Unique0 ?
Unique (%)0.0%

Sample

1st row장애유형
2nd row합계
3rd row지체
4th row시각
5th row청각
ValueCountFrequency (%)
장애유형 2
 
5.9%
정신 2
 
5.9%
장루.요루 2
 
5.9%
안면 2
 
5.9%
간 2
 
5.9%
호흡기 2
 
5.9%
심장 2
 
5.9%
신장 2
 
5.9%
자폐성 2
 
5.9%
합계 2
 
5.9%
Other values (7) 14
41.2%
2024-03-14T10:00:02.602044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 8
 
9.5%
루 4
 
4.8%
신 4
 
4.8%
뇌 4
 
4.8%
지 4
 
4.8%
각 4
 
4.8%
. 2
 
2.4%
면 2
 
2.4%
안 2
 
2.4%
성 2
 
2.4%
Other values (24) 48
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82
97.6%
Other Punctuation 2
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 8
 
9.8%
루 4
 
4.9%
신 4
 
4.9%
뇌 4
 
4.9%
지 4
 
4.9%
각 4
 
4.9%
면 2
 
2.4%
안 2
 
2.4%
성 2
 
2.4%
간 2
 
2.4%
Other values (23) 46
56.1%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82
97.6%
Common 2
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 8
 
9.8%
루 4
 
4.9%
신 4
 
4.9%
뇌 4
 
4.9%
지 4
 
4.9%
각 4
 
4.9%
면 2
 
2.4%
안 2
 
2.4%
성 2
 
2.4%
간 2
 
2.4%
Other values (23) 46
56.1%
Common
ValueCountFrequency (%)
. 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82
97.6%
ASCII 2
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 8
 
9.8%
루 4
 
4.9%
신 4
 
4.9%
뇌 4
 
4.9%
지 4
 
4.9%
각 4
 
4.9%
면 2
 
2.4%
안 2
 
2.4%
성 2
 
2.4%
간 2
 
2.4%
Other values (23) 46
56.1%
ASCII
ValueCountFrequency (%)
. 2
100.0%

Unnamed: 2
Text

MISSING 

Distinct17
Distinct (%)50.0%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-03-14T10:00:02.759787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3529412
Min length2

Characters and Unicode

Total characters182
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

Unique0 ?
Unique (%)0.0%

Sample

1st row합계
2nd row129,741
3rd row69,454
4th row11,866
5th row13,096
ValueCountFrequency (%)
합계 2
 
5.9%
5,388 2
 
5.9%
560 2
 
5.9%
118 2
 
5.9%
343 2
 
5.9%
372 2
 
5.9%
181 2
 
5.9%
2,429 2
 
5.9%
607 2
 
5.9%
129,741 2
 
5.9%
Other values (7) 14
41.2%
2024-03-14T10:00:03.024005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
17.6%
1 28
15.4%
, 18
9.9%
4 16
8.8%
2 14
7.7%
6 14
7.7%
3 14
7.7%
8 12
 
6.6%
9 8
 
4.4%
7 8
 
4.4%
Other values (4) 18
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128
70.3%
Space Separator 32
 
17.6%
Other Punctuation 18
 
9.9%
Other Letter 4
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28
21.9%
4 16
12.5%
2 14
10.9%
6 14
10.9%
3 14
10.9%
8 12
9.4%
9 8
 
6.2%
7 8
 
6.2%
5 8
 
6.2%
0 6
 
4.7%
Other Letter
ValueCountFrequency (%)
합 2
50.0%
계 2
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 178
97.8%
Hangul 4
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
32
18.0%
1 28
15.7%
, 18
10.1%
4 16
9.0%
2 14
7.9%
6 14
7.9%
3 14
7.9%
8 12
 
6.7%
9 8
 
4.5%
7 8
 
4.5%
Other values (2) 14
7.9%
Hangul
ValueCountFrequency (%)
합 2
50.0%
계 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178
97.8%
Hangul 4
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
18.0%
1 28
15.7%
, 18
10.1%
4 16
9.0%
2 14
7.9%
6 14
7.9%
3 14
7.9%
8 12
 
6.7%
9 8
 
4.5%
7 8
 
4.5%
Other values (2) 14
7.9%
Hangul
ValueCountFrequency (%)
합 2
50.0%
계 2
50.0%

Unnamed: 3
Text

MISSING 

Distinct30
Distinct (%)85.7%
Missing11
Missing (%)23.9%
Memory size500.0 B
2024-03-14T10:00:03.205436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6285714
Min length1

Characters and Unicode

Total characters127
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

Unique25 ?
Unique (%)71.4%

Sample

1st row1급
2nd row9,260
3rd row1,707
4th row1,363
5th row311
ValueCountFrequency (%)
10 2
 
5.7%
1급 2
 
5.7%
5 2
 
5.7%
8 2
 
5.7%
0 2
 
5.7%
81 1
 
2.9%
684 1
 
2.9%
1,631 1
 
2.9%
1,143 1
 
2.9%
184 1
 
2.9%
Other values (20) 20
57.1%
2024-03-14T10:00:03.521662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
25.2%
1 23
18.1%
, 9
 
7.1%
3 9
 
7.1%
8 8
 
6.3%
2 8
 
6.3%
0 7
 
5.5%
5 7
 
5.5%
6 7
 
5.5%
4 6
 
4.7%
Other values (4) 11
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
65.4%
Space Separator 32
 
25.2%
Other Punctuation 9
 
7.1%
Other Letter 3
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
27.7%
3 9
 
10.8%
8 8
 
9.6%
2 8
 
9.6%
0 7
 
8.4%
5 7
 
8.4%
6 7
 
8.4%
4 6
 
7.2%
9 4
 
4.8%
7 4
 
4.8%
Other Letter
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
97.6%
Hangul 3
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
32
25.8%
1 23
18.5%
, 9
 
7.3%
3 9
 
7.3%
8 8
 
6.5%
2 8
 
6.5%
0 7
 
5.6%
5 7
 
5.6%
6 7
 
5.6%
4 6
 
4.8%
Other values (2) 8
 
6.5%
Hangul
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
97.6%
Hangul 3
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
25.8%
1 23
18.5%
, 9
 
7.3%
3 9
 
7.3%
8 8
 
6.5%
2 8
 
6.5%
0 7
 
5.6%
5 7
 
5.6%
6 7
 
5.6%
4 6
 
4.8%
Other values (2) 8
 
6.5%
Hangul
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%

Unnamed: 4
Text

MISSING 

Distinct32
Distinct (%)94.1%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-03-14T10:00:03.683843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8235294
Min length1

Characters and Unicode

Total characters130
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

Unique30 ?
Unique (%)88.2%

Sample

1st row2급
2nd row17,299
3rd row3,863
4th row351
5th row2,134
ValueCountFrequency (%)
11 2
 
5.9%
0 2
 
5.9%
1,248 1
 
2.9%
4,068 1
 
2.9%
592 1
 
2.9%
679 1
 
2.9%
149 1
 
2.9%
4 1
 
2.9%
1,195 1
 
2.9%
20 1
 
2.9%
Other values (22) 22
64.7%
2024-03-14T10:00:04.046342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
24.6%
1 16
12.3%
4 13
10.0%
2 11
 
8.5%
, 10
 
7.7%
3 9
 
6.9%
9 8
 
6.2%
0 6
 
4.6%
7 6
 
4.6%
6 6
 
4.6%
Other values (4) 13
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86
66.2%
Space Separator 32
 
24.6%
Other Punctuation 10
 
7.7%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
18.6%
4 13
15.1%
2 11
12.8%
3 9
10.5%
9 8
9.3%
0 6
 
7.0%
7 6
 
7.0%
6 6
 
7.0%
5 6
 
7.0%
8 5
 
5.8%
Other Letter
ValueCountFrequency (%)
급 1
50.0%
여 1
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
32
25.0%
1 16
12.5%
4 13
10.2%
2 11
 
8.6%
, 10
 
7.8%
3 9
 
7.0%
9 8
 
6.2%
0 6
 
4.7%
7 6
 
4.7%
6 6
 
4.7%
Other values (2) 11
 
8.6%
Hangul
ValueCountFrequency (%)
급 1
50.0%
여 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
25.0%
1 16
12.5%
4 13
10.2%
2 11
 
8.6%
, 10
 
7.8%
3 9
 
7.0%
9 8
 
6.2%
0 6
 
4.7%
7 6
 
4.7%
6 6
 
4.7%
Other values (2) 11
 
8.6%
Hangul
ValueCountFrequency (%)
급 1
50.0%
여 1
50.0%

Unnamed: 5
Text

MISSING 

Distinct32
Distinct (%)94.1%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-03-14T10:00:04.221716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.0294118
Min length2

Characters and Unicode

Total characters137
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

Unique30 ?
Unique (%)88.2%

Sample

1st row3급
2nd row22,946
3rd row8,452
4th row609
5th row2,169
ValueCountFrequency (%)
0 2
 
5.9%
39 2
 
5.9%
2,338 1
 
2.9%
1,363 1
 
2.9%
311 1
 
2.9%
14 1
 
2.9%
2,879 1
 
2.9%
228 1
 
2.9%
9,260 1
 
2.9%
155 1
 
2.9%
Other values (22) 22
64.7%
2024-03-14T10:00:04.526803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
23.4%
9 13
9.5%
2 13
9.5%
1 13
9.5%
, 11
 
8.0%
0 9
 
6.6%
3 9
 
6.6%
4 8
 
5.8%
6 8
 
5.8%
5 7
 
5.1%
Other values (5) 14
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
66.4%
Space Separator 32
 
23.4%
Other Punctuation 11
 
8.0%
Other Letter 3
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 13
14.3%
2 13
14.3%
1 13
14.3%
0 9
9.9%
3 9
9.9%
4 8
8.8%
6 8
8.8%
5 7
7.7%
7 6
6.6%
8 5
 
5.5%
Other Letter
ValueCountFrequency (%)
합 1
33.3%
계 1
33.3%
급 1
33.3%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 134
97.8%
Hangul 3
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
32
23.9%
9 13
9.7%
2 13
9.7%
1 13
9.7%
, 11
 
8.2%
0 9
 
6.7%
3 9
 
6.7%
4 8
 
6.0%
6 8
 
6.0%
5 7
 
5.2%
Other values (2) 11
 
8.2%
Hangul
ValueCountFrequency (%)
합 1
33.3%
계 1
33.3%
급 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
97.8%
Hangul 3
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
23.9%
9 13
9.7%
2 13
9.7%
1 13
9.7%
, 11
 
8.2%
0 9
 
6.7%
3 9
 
6.7%
4 8
 
6.0%
6 8
 
6.0%
5 7
 
5.2%
Other values (2) 11
 
8.2%
Hangul
ValueCountFrequency (%)
합 1
33.3%
계 1
33.3%
급 1
33.3%

Unnamed: 6
Text

MISSING 

Distinct30
Distinct (%)85.7%
Missing11
Missing (%)23.9%
Memory size500.0 B
2024-03-14T10:00:04.726264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.7714286
Min length1

Characters and Unicode

Total characters132
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

Unique28 ?
Unique (%)80.0%

Sample

1st row4급
2nd row20,423
3rd row14,045
4th row622
5th row2,878
ValueCountFrequency (%)
0 5
 
14.3%
11 2
 
5.7%
9,787 1
 
2.9%
9 1
 
2.9%
78 1
 
2.9%
14 1
 
2.9%
1,010 1
 
2.9%
954 1
 
2.9%
232 1
 
2.9%
1,215 1
 
2.9%
Other values (20) 20
57.1%
2024-03-14T10:00:05.029512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
24.2%
1 16
12.1%
2 13
9.8%
0 12
 
9.1%
, 10
 
7.6%
8 9
 
6.8%
4 8
 
6.1%
9 7
 
5.3%
3 6
 
4.5%
7 6
 
4.5%
Other values (4) 13
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
65.9%
Space Separator 32
 
24.2%
Other Punctuation 10
 
7.6%
Other Letter 3
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
18.4%
2 13
14.9%
0 12
13.8%
8 9
10.3%
4 8
9.2%
9 7
8.0%
3 6
 
6.9%
7 6
 
6.9%
5 5
 
5.7%
6 5
 
5.7%
Other Letter
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 129
97.7%
Hangul 3
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
32
24.8%
1 16
12.4%
2 13
10.1%
0 12
 
9.3%
, 10
 
7.8%
8 9
 
7.0%
4 8
 
6.2%
9 7
 
5.4%
3 6
 
4.7%
7 6
 
4.7%
Other values (2) 10
 
7.8%
Hangul
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129
97.7%
Hangul 3
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
24.8%
1 16
12.4%
2 13
10.1%
0 12
 
9.3%
, 10
 
7.8%
8 9
 
7.0%
4 8
 
6.2%
9 7
 
5.4%
3 6
 
4.7%
7 6
 
4.7%
Other values (2) 10
 
7.8%
Hangul
ValueCountFrequency (%)
급 2
66.7%
남 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct29
Distinct (%)85.3%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-03-14T10:00:05.178793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.7352941
Min length1

Characters and Unicode

Total characters127
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

Unique27 ?
Unique (%)79.4%

Sample

1st row5급
2nd row28,291
3rd row21,138
4th row956
5th row3,555
ValueCountFrequency (%)
0 4
 
11.8%
2 3
 
8.8%
1,468 1
 
2.9%
7,512 1
 
2.9%
13 1
 
2.9%
25 1
 
2.9%
12 1
 
2.9%
647 1
 
2.9%
805 1
 
2.9%
48 1
 
2.9%
Other values (19) 19
55.9%
2024-03-14T10:00:05.416139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
25.2%
1 21
16.5%
5 14
11.0%
2 13
10.2%
, 9
 
7.1%
0 7
 
5.5%
4 7
 
5.5%
8 6
 
4.7%
9 5
 
3.9%
3 4
 
3.1%
Other values (4) 9
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
66.1%
Space Separator 32
 
25.2%
Other Punctuation 9
 
7.1%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
25.0%
5 14
16.7%
2 13
15.5%
0 7
 
8.3%
4 7
 
8.3%
8 6
 
7.1%
9 5
 
6.0%
3 4
 
4.8%
6 4
 
4.8%
7 3
 
3.6%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
급 1
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 125
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
32
25.6%
1 21
16.8%
5 14
11.2%
2 13
10.4%
, 9
 
7.2%
0 7
 
5.6%
4 7
 
5.6%
8 6
 
4.8%
9 5
 
4.0%
3 4
 
3.2%
Other values (2) 7
 
5.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
급 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
25.6%
1 21
16.8%
5 14
11.2%
2 13
10.4%
, 9
 
7.2%
0 7
 
5.6%
4 7
 
5.6%
8 6
 
4.8%
9 5
 
4.0%
3 4
 
3.2%
Other values (2) 7
 
5.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
급 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)71.4%
Missing11
Missing (%)23.9%
Memory size500.0 B
2024-03-14T10:00:05.534451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.9428571
Min length2

Characters and Unicode

Total characters138
Distinct characters21
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

Unique24 ?
Unique (%)68.6%

Sample

1st row(단위: 명)
2nd row6급
3rd row31,522
4th row20,249
5th row7,965
ValueCountFrequency (%)
0 11
30.6%
6급 1
 
2.8%
147 1
 
2.8%
2 1
 
2.8%
24 1
 
2.8%
11 1
 
2.8%
103 1
 
2.8%
26 1
 
2.8%
1,657 1
 
2.8%
1,759 1
 
2.8%
Other values (16) 16
44.4%
2024-03-14T10:00:05.834104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
23.9%
0 16
11.6%
2 14
10.1%
, 12
 
8.7%
1 11
 
8.0%
4 8
 
5.8%
9 8
 
5.8%
3 8
 
5.8%
5 6
 
4.3%
6 5
 
3.6%
Other values (11) 17
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
60.9%
Space Separator 33
 
23.9%
Other Punctuation 13
 
9.4%
Other Letter 6
 
4.3%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
19.0%
2 14
16.7%
1 11
13.1%
4 8
9.5%
9 8
9.5%
3 8
9.5%
5 6
 
7.1%
6 5
 
6.0%
7 5
 
6.0%
8 3
 
3.6%
Other Letter
ValueCountFrequency (%)
급 1
16.7%
합 1
16.7%
계 1
16.7%
단 1
16.7%
위 1
16.7%
명 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 12
92.3%
: 1
 
7.7%
Space Separator
ValueCountFrequency (%)
33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 132
95.7%
Hangul 6
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
33
25.0%
0 16
12.1%
2 14
10.6%
, 12
 
9.1%
1 11
 
8.3%
4 8
 
6.1%
9 8
 
6.1%
3 8
 
6.1%
5 6
 
4.5%
6 5
 
3.8%
Other values (5) 11
 
8.3%
Hangul
ValueCountFrequency (%)
급 1
16.7%
합 1
16.7%
계 1
16.7%
단 1
16.7%
위 1
16.7%
명 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
95.7%
Hangul 6
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33
25.0%
0 16
12.1%
2 14
10.6%
, 12
 
9.1%
1 11
 
8.3%
4 8
 
6.1%
9 8
 
6.1%
3 8
 
6.1%
5 6
 
4.5%
6 5
 
3.8%
Other values (5) 11
 
8.3%
Hangul
ValueCountFrequency (%)
급 1
16.7%
합 1
16.7%
계 1
16.7%
단 1
16.7%
위 1
16.7%
명 1
16.7%

Unnamed: 9
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing28
Missing (%)60.9%
Memory size500.0 B
2024-03-14T10:00:05.979659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4
Min length1

Characters and Unicode

Total characters72
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 (%)100.0%

Sample

1st row3급
2nd row남
3rd row13,567
4th row5,319
5th row302
ValueCountFrequency (%)
3급 1
 
5.6%
남 1
 
5.6%
30 1
 
5.6%
14 1
 
5.6%
12 1
 
5.6%
170 1
 
5.6%
74 1
 
5.6%
0 1
 
5.6%
1,792 1
 
5.6%
89 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:00:06.335591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
22.2%
3 8
11.1%
1 8
11.1%
, 6
 
8.3%
5 5
 
6.9%
7 5
 
6.9%
0 5
 
6.9%
2 5
 
6.9%
6 4
 
5.6%
9 4
 
5.6%
Other values (4) 6
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
66.7%
Space Separator 16
 
22.2%
Other Punctuation 6
 
8.3%
Other Letter 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 8
16.7%
1 8
16.7%
5 5
10.4%
7 5
10.4%
0 5
10.4%
2 5
10.4%
6 4
8.3%
9 4
8.3%
4 3
 
6.2%
8 1
 
2.1%
Other Letter
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
97.2%
Hangul 2
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
16
22.9%
3 8
11.4%
1 8
11.4%
, 6
 
8.6%
5 5
 
7.1%
7 5
 
7.1%
0 5
 
7.1%
2 5
 
7.1%
6 4
 
5.7%
9 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
97.2%
Hangul 2
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
22.9%
3 8
11.4%
1 8
11.4%
, 6
 
8.6%
5 5
 
7.1%
7 5
 
7.1%
0 5
 
7.1%
2 5
 
7.1%
6 4
 
5.7%
9 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Unnamed: 10
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:06.485511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.7647059
Min length1

Characters and Unicode

Total characters64
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 (%)100.0%

Sample

1st row여
2nd row9,379
3rd row3,133
4th row307
5th row939
ValueCountFrequency (%)
여 1
 
5.9%
1,682 1
 
5.9%
9 1
 
5.9%
25 1
 
5.9%
7 1
 
5.9%
51 1
 
5.9%
53 1
 
5.9%
0 1
 
5.9%
10 1
 
5.9%
9,379 1
 
5.9%
Other values (7) 7
41.2%
2024-03-14T10:00:06.750877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
25.0%
3 11
17.2%
1 7
10.9%
9 6
 
9.4%
, 5
 
7.8%
7 4
 
6.2%
0 4
 
6.2%
5 3
 
4.7%
6 2
 
3.1%
8 2
 
3.1%
Other values (3) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
65.6%
Space Separator 16
 
25.0%
Other Punctuation 5
 
7.8%
Other Letter 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
26.2%
1 7
16.7%
9 6
14.3%
7 4
 
9.5%
0 4
 
9.5%
5 3
 
7.1%
6 2
 
4.8%
8 2
 
4.8%
2 2
 
4.8%
4 1
 
2.4%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Other Letter
ValueCountFrequency (%)
여 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
98.4%
Hangul 1
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
16
25.4%
3 11
17.5%
1 7
11.1%
9 6
 
9.5%
, 5
 
7.9%
7 4
 
6.3%
0 4
 
6.3%
5 3
 
4.8%
6 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
98.4%
Hangul 1
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
25.4%
3 11
17.5%
1 7
11.1%
9 6
 
9.5%
, 5
 
7.9%
7 4
 
6.3%
0 4
 
6.3%
5 3
 
4.8%
6 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Unnamed: 11
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:06.901258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.2352941
Min length2

Characters and Unicode

Total characters72
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

Unique15 ?
Unique (%)88.2%

Sample

1st row합계
2nd row22,946
3rd row8,452
4th row609
5th row2,169
ValueCountFrequency (%)
39 2
 
11.8%
합계 1
 
5.9%
22,946 1
 
5.9%
8,452 1
 
5.9%
609 1
 
5.9%
2,169 1
 
5.9%
505 1
 
5.9%
4,156 1
 
5.9%
2,947 1
 
5.9%
3,474 1
 
5.9%
Other values (6) 6
35.3%
2024-03-14T10:00:07.148458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
22.2%
9 10
13.9%
2 8
11.1%
, 6
 
8.3%
4 6
 
8.3%
1 5
 
6.9%
6 4
 
5.6%
5 4
 
5.6%
0 4
 
5.6%
3 3
 
4.2%
Other values (4) 6
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
66.7%
Space Separator 16
 
22.2%
Other Punctuation 6
 
8.3%
Other Letter 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 10
20.8%
2 8
16.7%
4 6
12.5%
1 5
10.4%
6 4
 
8.3%
5 4
 
8.3%
0 4
 
8.3%
3 3
 
6.2%
7 3
 
6.2%
8 1
 
2.1%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
97.2%
Hangul 2
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
16
22.9%
9 10
14.3%
2 8
11.4%
, 6
 
8.6%
4 6
 
8.6%
1 5
 
7.1%
6 4
 
5.7%
5 4
 
5.7%
0 4
 
5.7%
3 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
97.2%
Hangul 2
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
22.9%
9 10
14.3%
2 8
11.4%
, 6
 
8.6%
4 6
 
8.6%
1 5
 
7.1%
6 4
 
5.7%
5 4
 
5.7%
0 4
 
5.7%
3 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 12
Text

MISSING 

Distinct15
Distinct (%)83.3%
Missing28
Missing (%)60.9%
Memory size500.0 B
2024-03-14T10:00:07.258677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.2777778
Min length1

Characters and Unicode

Total characters59
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 (%)77.8%

Sample

1st row4급
2nd row남
3rd row9,467
4th row5,904
5th row324
ValueCountFrequency (%)
0 4
22.2%
4급 1
 
5.6%
남 1
 
5.6%
9,467 1
 
5.6%
5,904 1
 
5.6%
324 1
 
5.6%
1,542 1
 
5.6%
317 1
 
5.6%
959 1
 
5.6%
16 1
 
5.6%
Other values (5) 5
27.8%
2024-03-14T10:00:07.481910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
27.1%
1 7
11.9%
4 6
 
10.2%
0 5
 
8.5%
9 5
 
8.5%
7 4
 
6.8%
, 3
 
5.1%
5 3
 
5.1%
3 3
 
5.1%
2 3
 
5.1%
Other values (3) 4
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
64.4%
Space Separator 16
27.1%
Other Punctuation 3
 
5.1%
Other Letter 2
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
18.4%
4 6
15.8%
0 5
13.2%
9 5
13.2%
7 4
10.5%
5 3
7.9%
3 3
7.9%
2 3
7.9%
6 2
 
5.3%
Other Letter
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
96.6%
Hangul 2
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
16
28.1%
1 7
12.3%
4 6
 
10.5%
0 5
 
8.8%
9 5
 
8.8%
7 4
 
7.0%
, 3
 
5.3%
5 3
 
5.3%
3 3
 
5.3%
2 3
 
5.3%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
96.6%
Hangul 2
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
28.1%
1 7
12.3%
4 6
 
10.5%
0 5
 
8.8%
9 5
 
8.8%
7 4
 
7.0%
, 3
 
5.3%
5 3
 
5.3%
3 3
 
5.3%
2 3
 
5.3%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Unnamed: 13
Text

MISSING 

Distinct13
Distinct (%)76.5%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:07.594014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.3529412
Min length1

Characters and Unicode

Total characters57
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

Unique12 ?
Unique (%)70.6%

Sample

1st row여
2nd row10,956
3rd row8,141
4th row298
5th row1,336
ValueCountFrequency (%)
0 5
29.4%
여 1
 
5.9%
10,956 1
 
5.9%
8,141 1
 
5.9%
298 1
 
5.9%
1,336 1
 
5.9%
151 1
 
5.9%
748 1
 
5.9%
5 1
 
5.9%
2 1
 
5.9%
Other values (3) 3
17.6%
2024-03-14T10:00:07.804161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
28.1%
1 8
14.0%
0 7
12.3%
3 4
 
7.0%
, 3
 
5.3%
5 3
 
5.3%
6 3
 
5.3%
8 3
 
5.3%
2 3
 
5.3%
9 2
 
3.5%
Other values (3) 5
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
64.9%
Space Separator 16
28.1%
Other Punctuation 3
 
5.3%
Other Letter 1
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
21.6%
0 7
18.9%
3 4
10.8%
5 3
 
8.1%
6 3
 
8.1%
8 3
 
8.1%
2 3
 
8.1%
9 2
 
5.4%
4 2
 
5.4%
7 2
 
5.4%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
여 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56
98.2%
Hangul 1
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
16
28.6%
1 8
14.3%
0 7
12.5%
3 4
 
7.1%
, 3
 
5.4%
5 3
 
5.4%
6 3
 
5.4%
8 3
 
5.4%
2 3
 
5.4%
9 2
 
3.6%
Other values (2) 4
 
7.1%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
98.2%
Hangul 1
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
28.6%
1 8
14.3%
0 7
12.5%
3 4
 
7.1%
, 3
 
5.4%
5 3
 
5.4%
6 3
 
5.4%
8 3
 
5.4%
2 3
 
5.4%
9 2
 
3.6%
Other values (2) 4
 
7.1%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Unnamed: 14
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:07.921883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.7058824
Min length2

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

Unique13 ?
Unique (%)76.5%

Sample

1st row합계
2nd row20,423
3rd row14,045
4th row622
5th row2,878
ValueCountFrequency (%)
0 4
23.5%
합계 1
 
5.9%
20,423 1
 
5.9%
14,045 1
 
5.9%
622 1
 
5.9%
2,878 1
 
5.9%
468 1
 
5.9%
1,707 1
 
5.9%
21 1
 
5.9%
1 1
 
5.9%
Other values (4) 4
23.5%
2024-03-14T10:00:08.353582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
25.4%
0 7
11.1%
2 7
11.1%
1 6
 
9.5%
4 5
 
7.9%
8 5
 
7.9%
, 4
 
6.3%
3 4
 
6.3%
7 3
 
4.8%
6 2
 
3.2%
Other values (4) 4
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41
65.1%
Space Separator 16
 
25.4%
Other Punctuation 4
 
6.3%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
17.1%
2 7
17.1%
1 6
14.6%
4 5
12.2%
8 5
12.2%
3 4
9.8%
7 3
7.3%
6 2
 
4.9%
5 1
 
2.4%
9 1
 
2.4%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
16
26.2%
0 7
11.5%
2 7
11.5%
1 6
 
9.8%
4 5
 
8.2%
8 5
 
8.2%
, 4
 
6.6%
3 4
 
6.6%
7 3
 
4.9%
6 2
 
3.3%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
26.2%
0 7
11.5%
2 7
11.5%
1 6
 
9.8%
4 5
 
8.2%
8 5
 
8.2%
, 4
 
6.6%
3 4
 
6.6%
7 3
 
4.9%
6 2
 
3.3%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 15
Text

MISSING 

Distinct14
Distinct (%)77.8%
Missing28
Missing (%)60.9%
Memory size500.0 B
2024-03-14T10:00:08.514255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.2777778
Min length1

Characters and Unicode

Total characters59
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

Unique12 ?
Unique (%)66.7%

Sample

1st row5급
2nd row남
3rd row13,544
4th row9,532
5th row508
ValueCountFrequency (%)
0 4
22.2%
1 2
11.1%
5급 1
 
5.6%
남 1
 
5.6%
13,544 1
 
5.6%
9,532 1
 
5.6%
508 1
 
5.6%
1,868 1
 
5.6%
914 1
 
5.6%
364 1
 
5.6%
Other values (4) 4
22.2%
2024-03-14T10:00:08.726151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
27.1%
0 6
 
10.2%
1 6
 
10.2%
5 4
 
6.8%
3 4
 
6.8%
4 4
 
6.8%
2 4
 
6.8%
, 3
 
5.1%
9 3
 
5.1%
8 3
 
5.1%
Other values (4) 6
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
64.4%
Space Separator 16
27.1%
Other Punctuation 3
 
5.1%
Other Letter 2
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
15.8%
1 6
15.8%
5 4
10.5%
3 4
10.5%
4 4
10.5%
2 4
10.5%
9 3
7.9%
8 3
7.9%
6 3
7.9%
7 1
 
2.6%
Other Letter
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
96.6%
Hangul 2
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
16
28.1%
0 6
 
10.5%
1 6
 
10.5%
5 4
 
7.0%
3 4
 
7.0%
4 4
 
7.0%
2 4
 
7.0%
, 3
 
5.3%
9 3
 
5.3%
8 3
 
5.3%
Other values (2) 4
 
7.0%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
96.6%
Hangul 2
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
28.1%
0 6
 
10.5%
1 6
 
10.5%
5 4
 
7.0%
3 4
 
7.0%
4 4
 
7.0%
2 4
 
7.0%
, 3
 
5.3%
9 3
 
5.3%
8 3
 
5.3%
Other values (2) 4
 
7.0%
Hangul
ValueCountFrequency (%)
급 1
50.0%
남 1
50.0%

Unnamed: 16
Text

MISSING 

Distinct13
Distinct (%)76.5%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:08.847151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.2941176
Min length1

Characters and Unicode

Total characters56
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

Unique12 ?
Unique (%)70.6%

Sample

1st row여
2nd row14,747
3rd row11,606
4th row448
5th row1,687
ValueCountFrequency (%)
0 5
29.4%
여 1
 
5.9%
14,747 1
 
5.9%
11,606 1
 
5.9%
448 1
 
5.9%
1,687 1
 
5.9%
618 1
 
5.9%
197 1
 
5.9%
5 1
 
5.9%
1 1
 
5.9%
Other values (3) 3
17.6%
2024-03-14T10:00:09.069392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
28.6%
1 9
16.1%
0 6
 
10.7%
7 5
 
8.9%
4 4
 
7.1%
6 4
 
7.1%
, 3
 
5.4%
8 3
 
5.4%
9 2
 
3.6%
여 1
 
1.8%
Other values (3) 3
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
64.3%
Space Separator 16
28.6%
Other Punctuation 3
 
5.4%
Other Letter 1
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
25.0%
0 6
16.7%
7 5
13.9%
4 4
11.1%
6 4
11.1%
8 3
 
8.3%
9 2
 
5.6%
5 1
 
2.8%
2 1
 
2.8%
3 1
 
2.8%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
여 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55
98.2%
Hangul 1
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
16
29.1%
1 9
16.4%
0 6
 
10.9%
7 5
 
9.1%
4 4
 
7.3%
6 4
 
7.3%
, 3
 
5.5%
8 3
 
5.5%
9 2
 
3.6%
5 1
 
1.8%
Other values (2) 2
 
3.6%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
98.2%
Hangul 1
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
29.1%
1 9
16.4%
0 6
 
10.9%
7 5
 
9.1%
4 4
 
7.3%
6 4
 
7.3%
, 3
 
5.5%
8 3
 
5.5%
9 2
 
3.6%
5 1
 
1.8%
Other values (2) 2
 
3.6%
Hangul
ValueCountFrequency (%)
여 1
100.0%

Unnamed: 17
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing29
Missing (%)63.0%
Memory size500.0 B
2024-03-14T10:00:09.180038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.6470588
Min length2

Characters and Unicode

Total characters62
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

Unique13 ?
Unique (%)76.5%

Sample

1st row합계
2nd row28,291
3rd row21,138
4th row956
5th row3,555
ValueCountFrequency (%)
0 4
23.5%
합계 1
 
5.9%
28,291 1
 
5.9%
21,138 1
 
5.9%
956 1
 
5.9%
3,555 1
 
5.9%
1,532 1
 
5.9%
561 1
 
5.9%
21 1
 
5.9%
2 1
 
5.9%
Other values (4) 4
23.5%
2024-03-14T10:00:09.400259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
25.8%
1 9
14.5%
2 7
11.3%
5 7
11.3%
0 5
 
8.1%
, 4
 
6.5%
8 3
 
4.8%
9 3
 
4.8%
3 3
 
4.8%
6 2
 
3.2%
Other values (3) 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
64.5%
Space Separator 16
 
25.8%
Other Punctuation 4
 
6.5%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
22.5%
2 7
17.5%
5 7
17.5%
0 5
12.5%
8 3
 
7.5%
9 3
 
7.5%
3 3
 
7.5%
6 2
 
5.0%
4 1
 
2.5%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
16
26.7%
1 9
15.0%
2 7
11.7%
5 7
11.7%
0 5
 
8.3%
, 4
 
6.7%
8 3
 
5.0%
9 3
 
5.0%
3 3
 
5.0%
6 2
 
3.3%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
26.7%
1 9
15.0%
2 7
11.7%
5 7
11.7%
0 5
 
8.3%
, 4
 
6.7%
8 3
 
5.0%
9 3
 
5.0%
3 3
 
5.0%
6 2
 
3.3%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 18
Text

MISSING 

Distinct10
Distinct (%)50.0%
Missing26
Missing (%)56.5%
Memory size500.0 B
2024-03-14T10:00:09.496518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length3.65
Min length1

Characters and Unicode

Total characters73
Distinct characters23
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

Unique9 ?
Unique (%)45.0%

Sample

1st row페이지 : 1 / 1
2nd row(단위: 명)
3rd row6급
4th row남
5th row19,059
ValueCountFrequency (%)
0 11
44.0%
2
 
8.0%
1 2
 
8.0%
페이지 1
 
4.0%
단위 1
 
4.0%
명 1
 
4.0%
6급 1
 
4.0%
남 1
 
4.0%
19,059 1
 
4.0%
12,182 1
 
4.0%
Other values (3) 3
 
12.0%
2024-03-14T10:00:09.688549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
28.8%
0 13
17.8%
1 8
 
11.0%
, 4
 
5.5%
9 3
 
4.1%
6 2
 
2.7%
4 2
 
2.7%
8 2
 
2.7%
2 2
 
2.7%
: 2
 
2.7%
Other values (13) 14
19.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
47.9%
Space Separator 21
28.8%
Other Letter 8
 
11.0%
Other Punctuation 7
 
9.6%
Close Punctuation 1
 
1.4%
Open Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
37.1%
1 8
22.9%
9 3
 
8.6%
6 2
 
5.7%
4 2
 
5.7%
8 2
 
5.7%
2 2
 
5.7%
5 2
 
5.7%
7 1
 
2.9%
Other Letter
ValueCountFrequency (%)
남 1
12.5%
급 1
12.5%
명 1
12.5%
위 1
12.5%
단 1
12.5%
지 1
12.5%
이 1
12.5%
페 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
: 2
28.6%
/ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
89.0%
Hangul 8
 
11.0%

Most frequent character per script

Common
ValueCountFrequency (%)
21
32.3%
0 13
20.0%
1 8
 
12.3%
, 4
 
6.2%
9 3
 
4.6%
6 2
 
3.1%
4 2
 
3.1%
8 2
 
3.1%
2 2
 
3.1%
: 2
 
3.1%
Other values (5) 6
 
9.2%
Hangul
ValueCountFrequency (%)
남 1
12.5%
급 1
12.5%
명 1
12.5%
위 1
12.5%
단 1
12.5%
지 1
12.5%
이 1
12.5%
페 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
89.0%
Hangul 8
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
32.3%
0 13
20.0%
1 8
 
12.3%
, 4
 
6.2%
9 3
 
4.6%
6 2
 
3.1%
4 2
 
3.1%
8 2
 
3.1%
2 2
 
3.1%
: 2
 
3.1%
Other values (5) 6
 
9.2%
Hangul
ValueCountFrequency (%)
남 1
12.5%
급 1
12.5%
명 1
12.5%
위 1
12.5%
단 1
12.5%
지 1
12.5%
이 1
12.5%
페 1
12.5%

Unnamed: 19
Categorical

Distinct8
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
29 
0
11 
여
 
1
12,463
 
1
8,067
 
1
Other values (3)
3 

Length

Max length7
Median length4
Mean length3.6086957
Min length1

Unique

Unique6 ?
Unique (%)13.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
63.0%
0 11
 
23.9%
여 1
 
2.2%
12,463 1
 
2.2%
8,067 1
 
2.2%
3,061 1
 
2.2%
893 1
 
2.2%
442 1
 
2.2%

Length

2024-03-14T10:00:09.793678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:00:09.896880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
63.0%
0 11
 
23.9%
여 1
 
2.2%
12,463 1
 
2.2%
8,067 1
 
2.2%
3,061 1
 
2.2%
893 1
 
2.2%
442 1
 
2.2%

Unnamed: 20
Categorical

Distinct8
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
29 
0
11 
합계
 
1
31,522
 
1
20,249
 
1
Other values (3)
3 

Length

Max length7
Median length4
Mean length3.7391304
Min length2

Unique

Unique6 ?
Unique (%)13.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
63.0%
0 11
 
23.9%
합계 1
 
2.2%
31,522 1
 
2.2%
20,249 1
 
2.2%
7,965 1
 
2.2%
2,049 1
 
2.2%
1,259 1
 
2.2%

Length

2024-03-14T10:00:10.024384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:00:10.129248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
63.0%
0 11
 
23.9%
합계 1
 
2.2%
31,522 1
 
2.2%
20,249 1
 
2.2%
7,965 1
 
2.2%
2,049 1
 
2.2%
1,259 1
 
2.2%

Sample

장애인 유형별, 등급별 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20
0(2015년 12월)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3전라북도<NA><NA><NA><NA><NA><NA><NA>(단위: 명)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5구분장애유형합계1급2급3급4급5급6급<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6전라북도합계129,7419,26017,29922,94620,42328,29131,522<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA>지체69,4541,7073,8638,45214,04521,13820,249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8<NA>시각11,8661,3633516096229567,965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA>청각13,0963112,1342,1692,8783,5552,049<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
장애인 유형별, 등급별 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20
36<NA>뇌병변12,2721,1431,1952,3381,2151,2742,4891,5691,3782,9479597481,7079146181,5328174421,259
37<NA>자폐성6071844422823248280891099000000000
38<NA>정신5,38881741559548051,7591,7921,6823,474000000000
39<NA>신장2,429127631901,0106471,65700016521364197561000
40<NA>심장181336141226745312710116521000
41<NA>호흡기372351146782510317051221000112000
42<NA>간343808921112719921122371294000
43<NA>안면118415111324142539173249101000
44<NA>장루.요루560000022309392311073389091181000
45<NA>뇌전증453551061420474390147136283272350000

Duplicate rows

Most frequently occurring

장애인 유형별, 등급별 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20# duplicates
1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5
0(2015년 12월)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2