Overview

Dataset statistics

Number of variables18
Number of observations49
Missing cells84
Missing cells (%)9.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory146.7 B

Variable types

Text13
Categorical5

Alerts

Unnamed: 4 is highly overall correlated with Unnamed: 5 and 3 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 16 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 17 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 14 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 4 is highly imbalanced (81.9%)Imbalance
Unnamed: 5 is highly imbalanced (78.5%)Imbalance
보급대상별 PC보급 현황 has 44 (89.8%) missing valuesMissing
Unnamed: 1 has 28 (57.1%) missing valuesMissing
Unnamed: 2 has 4 (8.2%) missing valuesMissing
Unnamed: 3 has 3 (6.1%) missing valuesMissing
Unnamed: 7 has 1 (2.0%) missing valuesMissing
Unnamed: 9 has 1 (2.0%) missing valuesMissing
Unnamed: 11 has 1 (2.0%) missing valuesMissing
Unnamed: 13 has 1 (2.0%) missing valuesMissing
Unnamed: 15 has 1 (2.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:13:56.911165
Analysis finished2024-03-14 02:13:58.342429
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보급대상별 PC보급 현황
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing44
Missing (%)89.8%
Memory size524.0 B
2024-03-14T11:13:58.415771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6
Min length2

Characters and Unicode

Total characters13
Distinct characters11
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

Unique5 ?
Unique (%)100.0%

Sample

1st row대분류
2nd row>개인
3rd row소계
4th row>단체
5th row합계
ValueCountFrequency (%)
대분류 1
20.0%
개인 1
20.0%
소계 1
20.0%
단체 1
20.0%
합계 1
20.0%
2024-03-14T11:13:58.625975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
> 2
15.4%
계 2
15.4%
대 1
7.7%
분 1
7.7%
류 1
7.7%
개 1
7.7%
인 1
7.7%
소 1
7.7%
단 1
7.7%
체 1
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
84.6%
Math Symbol 2
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 2
18.2%
대 1
9.1%
분 1
9.1%
류 1
9.1%
개 1
9.1%
인 1
9.1%
소 1
9.1%
단 1
9.1%
체 1
9.1%
합 1
9.1%
Math Symbol
ValueCountFrequency (%)
> 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
84.6%
Common 2
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 2
18.2%
대 1
9.1%
분 1
9.1%
류 1
9.1%
개 1
9.1%
인 1
9.1%
소 1
9.1%
단 1
9.1%
체 1
9.1%
합 1
9.1%
Common
ValueCountFrequency (%)
> 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
84.6%
ASCII 2
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
> 2
100.0%
Hangul
ValueCountFrequency (%)
계 2
18.2%
대 1
9.1%
분 1
9.1%
류 1
9.1%
개 1
9.1%
인 1
9.1%
소 1
9.1%
단 1
9.1%
체 1
9.1%
합 1
9.1%

Unnamed: 1
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing28
Missing (%)57.1%
Memory size524.0 B
2024-03-14T11:13:58.786190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length8
Mean length6
Min length2

Characters and Unicode

Total characters126
Distinct characters67
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

Unique21 ?
Unique (%)100.0%

Sample

1st row중분류
2nd row장애인
3rd row저소득층
4th row소년소녀가장
5th row국가유공자(상이등급판정자)
ValueCountFrequency (%)
중분류 1
 
4.3%
종합사회복지시설 1
 
4.3%
해외 1
 
4.3%
기타시설 1
 
4.3%
등 1
 
4.3%
시설(마을회관 1
 
4.3%
농어촌지역 1
 
4.3%
노인시설 1
 
4.3%
다문화가정지원센터 1
 
4.3%
국가유공자단체 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T11:13:59.053344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 6
 
4.8%
설 6
 
4.8%
시 6
 
4.8%
정 4
 
3.2%
인 4
 
3.2%
소 4
 
3.2%
이 4
 
3.2%
자 3
 
2.4%
한 3
 
2.4%
( 3
 
2.4%
Other values (57) 83
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
92.1%
Open Punctuation 3
 
2.4%
Close Punctuation 3
 
2.4%
Space Separator 2
 
1.6%
Decimal Number 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 6
 
5.2%
설 6
 
5.2%
시 6
 
5.2%
정 4
 
3.4%
인 4
 
3.4%
소 4
 
3.4%
이 4
 
3.4%
자 3
 
2.6%
한 3
 
2.6%
장 3
 
2.6%
Other values (52) 73
62.9%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
5 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116
92.1%
Common 10
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 6
 
5.2%
설 6
 
5.2%
시 6
 
5.2%
정 4
 
3.4%
인 4
 
3.4%
소 4
 
3.4%
이 4
 
3.4%
자 3
 
2.6%
한 3
 
2.6%
장 3
 
2.6%
Other values (52) 73
62.9%
Common
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
2
20.0%
6 1
 
10.0%
5 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116
92.1%
ASCII 10
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 6
 
5.2%
설 6
 
5.2%
시 6
 
5.2%
정 4
 
3.4%
인 4
 
3.4%
소 4
 
3.4%
이 4
 
3.4%
자 3
 
2.6%
한 3
 
2.6%
장 3
 
2.6%
Other values (52) 73
62.9%
ASCII
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
2
20.0%
6 1
 
10.0%
5 1
 
10.0%

Unnamed: 2
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing4
Missing (%)8.2%
Memory size524.0 B
2024-03-14T11:13:59.246819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.0666667
Min length2

Characters and Unicode

Total characters273
Distinct characters100
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row소분류
2nd row시각장애인
3rd row청각장애인
4th row지체장애인
5th row기타장애인
ValueCountFrequency (%)
기타 3
 
5.7%
다문화가정 1
 
1.9%
노인대학 1
 
1.9%
어린이보육원 1
 
1.9%
고아원 1
 
1.9%
아동시설 1
 
1.9%
국가유공자 1
 
1.9%
단체 1
 
1.9%
이주여성시설 1
 
1.9%
결혼이민자시설 1
 
1.9%
Other values (41) 41
77.4%
2024-03-14T11:13:59.840619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 14
 
5.1%
인 12
 
4.4%
설 12
 
4.4%
기 11
 
4.0%
타 9
 
3.3%
장 9
 
3.3%
애 8
 
2.9%
8
 
2.9%
이 7
 
2.6%
민 6
 
2.2%
Other values (90) 177
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 253
92.7%
Space Separator 8
 
2.9%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Uppercase Letter 3
 
1.1%
Decimal Number 2
 
0.7%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 14
 
5.5%
인 12
 
4.7%
설 12
 
4.7%
기 11
 
4.3%
타 9
 
3.6%
장 9
 
3.6%
애 8
 
3.2%
이 7
 
2.8%
민 6
 
2.4%
자 6
 
2.4%
Other values (81) 159
62.8%
Uppercase Letter
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
O 1
33.3%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 253
92.7%
Common 17
 
6.2%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 14
 
5.5%
인 12
 
4.7%
설 12
 
4.7%
기 11
 
4.3%
타 9
 
3.6%
장 9
 
3.6%
애 8
 
3.2%
이 7
 
2.8%
민 6
 
2.4%
자 6
 
2.4%
Other values (81) 159
62.8%
Common
ValueCountFrequency (%)
8
47.1%
( 3
 
17.6%
) 3
 
17.6%
, 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
Latin
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
O 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 253
92.7%
ASCII 20
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 14
 
5.5%
인 12
 
4.7%
설 12
 
4.7%
기 11
 
4.3%
타 9
 
3.6%
장 9
 
3.6%
애 8
 
3.2%
이 7
 
2.8%
민 6
 
2.4%
자 6
 
2.4%
Other values (81) 159
62.8%
ASCII
ValueCountFrequency (%)
8
40.0%
( 3
 
15.0%
) 3
 
15.0%
, 1
 
5.0%
N 1
 
5.0%
G 1
 
5.0%
O 1
 
5.0%
5 1
 
5.0%
6 1
 
5.0%

Unnamed: 3
Text

MISSING 

Distinct46
Distinct (%)100.0%
Missing3
Missing (%)6.1%
Memory size524.0 B
2024-03-14T11:14:00.052637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length1

Characters and Unicode

Total characters138
Distinct characters16
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row보급코드
2nd rowA11
3rd rowA12
4th rowA13
5th rowA14
ValueCountFrequency (%)
a51 1
 
2.2%
보급코드 1
 
2.2%
b31 1
 
2.2%
b32 1
 
2.2%
b33 1
 
2.2%
b41 1
 
2.2%
b51 1
 
2.2%
b52 1
 
2.2%
b53 1
 
2.2%
b54 1
 
2.2%
Other values (36) 36
78.3%
2024-03-14T11:14:00.351706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 29
21.0%
1 25
18.1%
2 17
12.3%
A 15
10.9%
3 11
 
8.0%
4 8
 
5.8%
9 8
 
5.8%
5 6
 
4.3%
8 6
 
4.3%
6 5
 
3.6%
Other values (6) 8
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
65.2%
Uppercase Letter 44
31.9%
Other Letter 4
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
27.8%
2 17
18.9%
3 11
12.2%
4 8
 
8.9%
9 8
 
8.9%
5 6
 
6.7%
8 6
 
6.7%
6 5
 
5.6%
7 2
 
2.2%
0 2
 
2.2%
Other Letter
ValueCountFrequency (%)
보 1
25.0%
급 1
25.0%
코 1
25.0%
드 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 29
65.9%
A 15
34.1%

Most occurring scripts

ValueCountFrequency (%)
Common 90
65.2%
Latin 44
31.9%
Hangul 4
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
27.8%
2 17
18.9%
3 11
12.2%
4 8
 
8.9%
9 8
 
8.9%
5 6
 
6.7%
8 6
 
6.7%
6 5
 
5.6%
7 2
 
2.2%
0 2
 
2.2%
Hangul
ValueCountFrequency (%)
보 1
25.0%
급 1
25.0%
코 1
25.0%
드 1
25.0%
Latin
ValueCountFrequency (%)
B 29
65.9%
A 15
34.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
97.1%
Hangul 4
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 29
21.6%
1 25
18.7%
2 17
12.7%
A 15
11.2%
3 11
 
8.2%
4 8
 
6.0%
9 8
 
6.0%
5 6
 
4.5%
8 6
 
4.5%
6 5
 
3.7%
Other values (2) 4
 
3.0%
Hangul
ValueCountFrequency (%)
보 1
25.0%
급 1
25.0%
코 1
25.0%
드 1
25.0%

Unnamed: 4
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
47 
2009
 
1
단체/개인
 
1

Length

Max length5
Median length1
Mean length1.1428571
Min length1

Unique

Unique2 ?
Unique (%)4.1%

Sample

1st row2009
2nd row단체/개인
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 47
95.9%
2009 1
 
2.0%
단체/개인 1
 
2.0%

Length

2024-03-14T11:14:00.480745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:00.577281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 47
95.9%
2009 1
 
2.0%
단체/개인 1
 
2.0%

Unnamed: 5
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
46 
<NA>
 
1
수량
 
1
828
 
1

Length

Max length4
Median length1
Mean length1.122449
Min length1

Unique

Unique3 ?
Unique (%)6.1%

Sample

1st row<NA>
2nd row수량
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46
93.9%
<NA> 1
 
2.0%
수량 1
 
2.0%
828 1
 
2.0%

Length

2024-03-14T11:14:00.657933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:00.733408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46
93.9%
na 1
 
2.0%
수량 1
 
2.0%
828 1
 
2.0%

Unnamed: 6
Text

Distinct25
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T11:14:00.818970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6530612
Min length1

Characters and Unicode

Total characters81
Distinct characters15
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

Unique19 ?
Unique (%)38.8%

Sample

1st row2010
2nd row단체/개인
3rd row75
4th row20
5th row241
ValueCountFrequency (%)
0 17
34.7%
2 4
 
8.2%
8 3
 
6.1%
20 2
 
4.1%
4 2
 
4.1%
18 2
 
4.1%
6 1
 
2.0%
240 1
 
2.0%
30 1
 
2.0%
12 1
 
2.0%
Other values (15) 15
30.6%
2024-03-14T11:14:01.035366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26
32.1%
2 12
14.8%
8 9
 
11.1%
1 9
 
11.1%
4 7
 
8.6%
7 4
 
4.9%
6 4
 
4.9%
5 2
 
2.5%
3 2
 
2.5%
9 1
 
1.2%
Other values (5) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
93.8%
Other Letter 4
 
4.9%
Other Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
34.2%
2 12
15.8%
8 9
 
11.8%
1 9
 
11.8%
4 7
 
9.2%
7 4
 
5.3%
6 4
 
5.3%
5 2
 
2.6%
3 2
 
2.6%
9 1
 
1.3%
Other Letter
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
95.1%
Hangul 4
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26
33.8%
2 12
15.6%
8 9
 
11.7%
1 9
 
11.7%
4 7
 
9.1%
7 4
 
5.2%
6 4
 
5.2%
5 2
 
2.6%
3 2
 
2.6%
9 1
 
1.3%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
95.1%
Hangul 4
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26
33.8%
2 12
15.6%
8 9
 
11.7%
1 9
 
11.7%
4 7
 
9.1%
7 4
 
5.2%
6 4
 
5.2%
5 2
 
2.6%
3 2
 
2.6%
9 1
 
1.3%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Unnamed: 7
Text

MISSING 

Distinct27
Distinct (%)56.2%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-14T11:14:01.149191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.7916667
Min length1

Characters and Unicode

Total characters86
Distinct characters12
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

Unique23 ?
Unique (%)47.9%

Sample

1st row수량
2nd row75
3rd row20
4th row241
5th row77
ValueCountFrequency (%)
0 17
35.4%
6 3
 
6.2%
10 3
 
6.2%
80 2
 
4.2%
88 1
 
2.1%
170 1
 
2.1%
1526 1
 
2.1%
172 1
 
2.1%
240 1
 
2.1%
18 1
 
2.1%
Other values (17) 17
35.4%
2024-03-14T11:14:01.411816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
32.6%
1 10
 
11.6%
2 10
 
11.6%
5 8
 
9.3%
4 7
 
8.1%
6 6
 
7.0%
8 6
 
7.0%
7 5
 
5.8%
9 2
 
2.3%
3 2
 
2.3%
Other values (2) 2
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
97.7%
Other Letter 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
33.3%
1 10
 
11.9%
2 10
 
11.9%
5 8
 
9.5%
4 7
 
8.3%
6 6
 
7.1%
8 6
 
7.1%
7 5
 
6.0%
9 2
 
2.4%
3 2
 
2.4%
Other Letter
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
97.7%
Hangul 2
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
33.3%
1 10
 
11.9%
2 10
 
11.9%
5 8
 
9.5%
4 7
 
8.3%
6 6
 
7.1%
8 6
 
7.1%
7 5
 
6.0%
9 2
 
2.4%
3 2
 
2.4%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
97.7%
Hangul 2
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
33.3%
1 10
 
11.9%
2 10
 
11.9%
5 8
 
9.5%
4 7
 
8.3%
6 6
 
7.1%
8 6
 
7.1%
7 5
 
6.0%
9 2
 
2.4%
3 2
 
2.4%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Unnamed: 8
Text

Distinct26
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T11:14:01.526968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6326531
Min length1

Characters and Unicode

Total characters80
Distinct characters15
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

Unique21 ?
Unique (%)42.9%

Sample

1st row2011
2nd row단체/개인
3rd row16
4th row11
5th row95
ValueCountFrequency (%)
0 17
34.7%
2 4
 
8.2%
12 3
 
6.1%
39 2
 
4.1%
5 2
 
4.1%
30 1
 
2.0%
6 1
 
2.0%
237 1
 
2.0%
22 1
 
2.0%
10 1
 
2.0%
Other values (16) 16
32.7%
2024-03-14T11:14:01.850835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
26.2%
2 13
16.2%
1 12
15.0%
5 6
 
7.5%
7 6
 
7.5%
4 5
 
6.2%
3 4
 
5.0%
9 3
 
3.8%
8 3
 
3.8%
6 2
 
2.5%
Other values (5) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
93.8%
Other Letter 4
 
5.0%
Other Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
28.0%
2 13
17.3%
1 12
16.0%
5 6
 
8.0%
7 6
 
8.0%
4 5
 
6.7%
3 4
 
5.3%
9 3
 
4.0%
8 3
 
4.0%
6 2
 
2.7%
Other Letter
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
95.0%
Hangul 4
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
27.6%
2 13
17.1%
1 12
15.8%
5 6
 
7.9%
7 6
 
7.9%
4 5
 
6.6%
3 4
 
5.3%
9 3
 
3.9%
8 3
 
3.9%
6 2
 
2.6%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
95.0%
Hangul 4
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
27.6%
2 13
17.1%
1 12
15.8%
5 6
 
7.9%
7 6
 
7.9%
4 5
 
6.6%
3 4
 
5.3%
9 3
 
3.9%
8 3
 
3.9%
6 2
 
2.6%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Unnamed: 9
Text

MISSING 

Distinct27
Distinct (%)56.2%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-14T11:14:01.970368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length1.6875
Min length1

Characters and Unicode

Total characters81
Distinct characters12
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

Unique22 ?
Unique (%)45.8%

Sample

1st row수량
2nd row16
3rd row11
4th row95
5th row48
ValueCountFrequency (%)
0 17
35.4%
48 3
 
6.2%
39 2
 
4.2%
5 2
 
4.2%
10 2
 
4.2%
332 1
 
2.1%
68 1
 
2.1%
907 1
 
2.1%
60 1
 
2.1%
50 1
 
2.1%
Other values (17) 17
35.4%
2024-03-14T11:14:02.215952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
28.4%
1 10
12.3%
4 9
 
11.1%
5 7
 
8.6%
7 6
 
7.4%
6 6
 
7.4%
3 5
 
6.2%
2 5
 
6.2%
8 4
 
4.9%
9 4
 
4.9%
Other values (2) 2
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
97.5%
Other Letter 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
29.1%
1 10
12.7%
4 9
 
11.4%
5 7
 
8.9%
7 6
 
7.6%
6 6
 
7.6%
3 5
 
6.3%
2 5
 
6.3%
8 4
 
5.1%
9 4
 
5.1%
Other Letter
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79
97.5%
Hangul 2
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
29.1%
1 10
12.7%
4 9
 
11.4%
5 7
 
8.9%
7 6
 
7.6%
6 6
 
7.6%
3 5
 
6.3%
2 5
 
6.3%
8 4
 
5.1%
9 4
 
5.1%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
97.5%
Hangul 2
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
29.1%
1 10
12.7%
4 9
 
11.4%
5 7
 
8.9%
7 6
 
7.6%
6 6
 
7.6%
3 5
 
6.3%
2 5
 
6.3%
8 4
 
5.1%
9 4
 
5.1%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Unnamed: 10
Text

Distinct25
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T11:14:02.339540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6122449
Min length1

Characters and Unicode

Total characters79
Distinct characters15
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

Unique19 ?
Unique (%)38.8%

Sample

1st row2012
2nd row단체/개인
3rd row19
4th row2
5th row45
ValueCountFrequency (%)
0 14
28.6%
1 4
 
8.2%
4 3
 
6.1%
2 3
 
6.1%
15 3
 
6.1%
3 3
 
6.1%
57 1
 
2.0%
196 1
 
2.0%
13 1
 
2.0%
8 1
 
2.0%
Other values (15) 15
30.6%
2024-03-14T11:14:02.574028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
22.8%
1 15
19.0%
3 8
10.1%
4 7
 
8.9%
2 7
 
8.9%
5 6
 
7.6%
7 4
 
5.1%
9 4
 
5.1%
6 3
 
3.8%
8 2
 
2.5%
Other values (5) 5
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
93.7%
Other Letter 4
 
5.1%
Other Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
24.3%
1 15
20.3%
3 8
10.8%
4 7
 
9.5%
2 7
 
9.5%
5 6
 
8.1%
7 4
 
5.4%
9 4
 
5.4%
6 3
 
4.1%
8 2
 
2.7%
Other Letter
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
94.9%
Hangul 4
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
24.0%
1 15
20.0%
3 8
10.7%
4 7
 
9.3%
2 7
 
9.3%
5 6
 
8.0%
7 4
 
5.3%
9 4
 
5.3%
6 3
 
4.0%
8 2
 
2.7%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
94.9%
Hangul 4
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
24.0%
1 15
20.0%
3 8
10.7%
4 7
 
9.3%
2 7
 
9.3%
5 6
 
8.0%
7 4
 
5.3%
9 4
 
5.3%
6 3
 
4.0%
8 2
 
2.7%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Unnamed: 11
Text

MISSING 

Distinct28
Distinct (%)58.3%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-14T11:14:02.695877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3.5
Mean length1.6458333
Min length1

Characters and Unicode

Total characters79
Distinct characters12
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

Unique20 ?
Unique (%)41.7%

Sample

1st row수량
2nd row19
3rd row2
4th row45
5th row190
ValueCountFrequency (%)
0 14
29.2%
3 2
 
4.2%
14 2
 
4.2%
15 2
 
4.2%
1 2
 
4.2%
10 2
 
4.2%
12 2
 
4.2%
6 2
 
4.2%
50 1
 
2.1%
43 1
 
2.1%
Other values (18) 18
37.5%
2024-03-14T11:14:02.921959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
22.8%
1 14
17.7%
3 8
10.1%
4 8
10.1%
5 8
10.1%
2 7
 
8.9%
6 4
 
5.1%
8 4
 
5.1%
9 4
 
5.1%
7 2
 
2.5%
Other values (2) 2
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
97.5%
Other Letter 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
23.4%
1 14
18.2%
3 8
10.4%
4 8
10.4%
5 8
10.4%
2 7
 
9.1%
6 4
 
5.2%
8 4
 
5.2%
9 4
 
5.2%
7 2
 
2.6%
Other Letter
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
97.5%
Hangul 2
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
23.4%
1 14
18.2%
3 8
10.4%
4 8
10.4%
5 8
10.4%
2 7
 
9.1%
6 4
 
5.2%
8 4
 
5.2%
9 4
 
5.2%
7 2
 
2.6%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
97.5%
Hangul 2
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
23.4%
1 14
18.2%
3 8
10.4%
4 8
10.4%
5 8
10.4%
2 7
 
9.1%
6 4
 
5.2%
8 4
 
5.2%
9 4
 
5.2%
7 2
 
2.6%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Unnamed: 12
Text

Distinct25
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T11:14:03.036180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6122449
Min length1

Characters and Unicode

Total characters79
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

Unique21 ?
Unique (%)42.9%

Sample

1st row2013
2nd row단체/개인
3rd row33
4th row15
5th row134
ValueCountFrequency (%)
0 18
36.7%
1 6
 
12.2%
3 2
 
4.1%
2 2
 
4.1%
858 1
 
2.0%
2013 1
 
2.0%
8 1
 
2.0%
101 1
 
2.0%
12 1
 
2.0%
9 1
 
2.0%
Other values (15) 15
30.6%
2024-03-14T11:14:03.261802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
26.6%
1 17
21.5%
3 9
11.4%
2 7
 
8.9%
9 6
 
7.6%
5 5
 
6.3%
4 4
 
5.1%
8 4
 
5.1%
단 1
 
1.3%
체 1
 
1.3%
Other values (4) 4
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
93.7%
Other Letter 4
 
5.1%
Other Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
28.4%
1 17
23.0%
3 9
12.2%
2 7
 
9.5%
9 6
 
8.1%
5 5
 
6.8%
4 4
 
5.4%
8 4
 
5.4%
7 1
 
1.4%
Other Letter
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
94.9%
Hangul 4
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
28.0%
1 17
22.7%
3 9
12.0%
2 7
 
9.3%
9 6
 
8.0%
5 5
 
6.7%
4 4
 
5.3%
8 4
 
5.3%
/ 1
 
1.3%
7 1
 
1.3%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
94.9%
Hangul 4
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
28.0%
1 17
22.7%
3 9
12.0%
2 7
 
9.3%
9 6
 
8.0%
5 5
 
6.7%
4 4
 
5.3%
8 4
 
5.3%
/ 1
 
1.3%
7 1
 
1.3%
Hangul
ValueCountFrequency (%)
단 1
25.0%
체 1
25.0%
개 1
25.0%
인 1
25.0%

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)54.2%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-14T11:14:03.385269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.5625
Min length1

Characters and Unicode

Total characters75
Distinct characters12
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

Unique20 ?
Unique (%)41.7%

Sample

1st row수량
2nd row33
3rd row15
4th row134
5th row89
ValueCountFrequency (%)
0 18
37.5%
1 2
 
4.2%
6 2
 
4.2%
3 2
 
4.2%
8 2
 
4.2%
5 2
 
4.2%
11 1
 
2.1%
728 1
 
2.1%
331 1
 
2.1%
48 1
 
2.1%
Other values (16) 16
33.3%
2024-03-14T11:14:03.615179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
26.7%
1 13
17.3%
3 11
14.7%
8 6
 
8.0%
4 6
 
8.0%
5 5
 
6.7%
9 5
 
6.7%
6 3
 
4.0%
2 2
 
2.7%
7 2
 
2.7%
Other values (2) 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
97.3%
Other Letter 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
27.4%
1 13
17.8%
3 11
15.1%
8 6
 
8.2%
4 6
 
8.2%
5 5
 
6.8%
9 5
 
6.8%
6 3
 
4.1%
2 2
 
2.7%
7 2
 
2.7%
Other Letter
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
97.3%
Hangul 2
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
27.4%
1 13
17.8%
3 11
15.1%
8 6
 
8.2%
4 6
 
8.2%
5 5
 
6.8%
9 5
 
6.8%
6 3
 
4.1%
2 2
 
2.7%
7 2
 
2.7%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
97.3%
Hangul 2
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
27.4%
1 13
17.8%
3 11
15.1%
8 6
 
8.2%
4 6
 
8.2%
5 5
 
6.8%
9 5
 
6.8%
6 3
 
4.1%
2 2
 
2.7%
7 2
 
2.7%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Unnamed: 14
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
18 
1
7 
2
3 
21
2 
50
 
1
Other values (18)
18 

Length

Max length5
Median length1
Mean length1.5714286
Min length1

Unique

Unique19 ?
Unique (%)38.8%

Sample

1st row2014
2nd row단체/개인
3rd row15
4th row12
5th row113

Common Values

ValueCountFrequency (%)
0 18
36.7%
1 7
 
14.3%
2 3
 
6.1%
21 2
 
4.1%
50 1
 
2.0%
15 1
 
2.0%
12 1
 
2.0%
113 1
 
2.0%
51 1
 
2.0%
273 1
 
2.0%
Other values (13) 13
26.5%

Length

2024-03-14T11:14:03.739877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 18
36.7%
1 7
 
14.3%
2 3
 
6.1%
21 2
 
4.1%
728 1
 
2.0%
2014 1
 
2.0%
83 1
 
2.0%
10 1
 
2.0%
7 1
 
2.0%
17 1
 
2.0%
Other values (13) 13
26.5%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)52.1%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-14T11:14:03.903657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.5208333
Min length1

Characters and Unicode

Total characters73
Distinct characters12
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

Unique20 ?
Unique (%)41.7%

Sample

1st row수량
2nd row15
3rd row12
4th row113
5th row51
ValueCountFrequency (%)
0 18
37.5%
3 4
 
8.3%
2 2
 
4.2%
1 2
 
4.2%
6 2
 
4.2%
수량 1
 
2.1%
216 1
 
2.1%
27 1
 
2.1%
18 1
 
2.1%
31 1
 
2.1%
Other values (15) 15
31.2%
2024-03-14T11:14:04.173365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
26.0%
1 14
19.2%
2 9
12.3%
3 8
11.0%
5 5
 
6.8%
7 5
 
6.8%
6 4
 
5.5%
4 4
 
5.5%
9 2
 
2.7%
수 1
 
1.4%
Other values (2) 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
97.3%
Other Letter 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
26.8%
1 14
19.7%
2 9
12.7%
3 8
11.3%
5 5
 
7.0%
7 5
 
7.0%
6 4
 
5.6%
4 4
 
5.6%
9 2
 
2.8%
8 1
 
1.4%
Other Letter
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
97.3%
Hangul 2
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
26.8%
1 14
19.7%
2 9
12.7%
3 8
11.3%
5 5
 
7.0%
7 5
 
7.0%
6 4
 
5.6%
4 4
 
5.6%
9 2
 
2.8%
8 1
 
1.4%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
97.3%
Hangul 2
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
26.8%
1 14
19.7%
2 9
12.7%
3 8
11.3%
5 5
 
7.0%
7 5
 
7.0%
6 4
 
5.6%
4 4
 
5.6%
9 2
 
2.8%
8 1
 
1.4%
Hangul
ValueCountFrequency (%)
수 1
50.0%
량 1
50.0%

Unnamed: 16
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
22 
1
6 
13
 
2
23
 
2
9
 
2
Other values (14)
15 

Length

Max length9
Median length1
Mean length1.6326531
Min length1

Unique

Unique13 ?
Unique (%)26.5%

Sample

1st row2015.10월말
2nd row단체/개인
3rd row15
4th row5
5th row103

Common Values

ValueCountFrequency (%)
0 22
44.9%
1 6
 
12.2%
13 2
 
4.1%
23 2
 
4.1%
9 2
 
4.1%
22 2
 
4.1%
53 1
 
2.0%
15 1
 
2.0%
5 1
 
2.0%
103 1
 
2.0%
Other values (9) 9
18.4%

Length

2024-03-14T11:14:04.289705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 22
44.9%
1 6
 
12.2%
13 2
 
4.1%
23 2
 
4.1%
9 2
 
4.1%
22 2
 
4.1%
571 1
 
2.0%
72 1
 
2.0%
12 1
 
2.0%
2 1
 
2.0%
Other values (9) 9
18.4%

Unnamed: 17
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
22 
3
4 
23
 
2
<NA>
 
2
15
 
1
Other values (18)
18 

Length

Max length4
Median length1
Mean length1.5510204
Min length1

Unique

Unique19 ?
Unique (%)38.8%

Sample

1st row<NA>
2nd row수량
3rd row15
4th row5
5th row103

Common Values

ValueCountFrequency (%)
0 22
44.9%
3 4
 
8.2%
23 2
 
4.1%
<NA> 2
 
4.1%
15 1
 
2.0%
243 1
 
2.0%
53 1
 
2.0%
1 1
 
2.0%
13 1
 
2.0%
5 1
 
2.0%
Other values (13) 13
26.5%

Length

2024-03-14T11:14:04.428809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 22
44.9%
3 4
 
8.2%
23 2
 
4.1%
na 2
 
4.1%
34 1
 
2.0%
103 1
 
2.0%
4 1
 
2.0%
263 1
 
2.0%
49 1
 
2.0%
6 1
 
2.0%
Other values (13) 13
26.5%

Correlations

2024-03-14T11:14:04.514510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보급대상별 PC보급 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
보급대상별 PC보급 현황1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.000NaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 61.0001.0001.0001.0001.0001.0001.0000.9920.9710.9730.9900.9720.9950.9780.9830.9840.9900.985
Unnamed: 71.0001.0001.0001.0001.0001.0000.9921.0000.9770.9900.9720.9690.9810.9730.9910.9850.9960.985
Unnamed: 81.0001.0001.0001.0001.0001.0000.9710.9771.0000.9960.9770.9770.9810.9730.9830.9910.9790.974
Unnamed: 91.0001.0001.0001.0001.0001.0000.9730.9900.9961.0000.9740.9640.9800.9720.9820.9770.9810.981
Unnamed: 101.0001.0001.0001.0001.0001.0000.9900.9720.9770.9741.0000.9950.9950.9840.9860.9850.9820.974
Unnamed: 111.0001.0001.0001.0001.0001.0000.9720.9690.9770.9640.9951.0000.9880.9850.9870.9860.9890.981
Unnamed: 121.0001.0001.0001.0001.0001.0000.9950.9810.9810.9800.9950.9881.0000.9960.9940.9930.9930.990
Unnamed: 131.0001.0001.0001.0001.0001.0000.9780.9730.9730.9720.9840.9850.9961.0000.9940.9910.9930.987
Unnamed: 141.0001.0001.0001.0001.0001.0000.9830.9910.9830.9820.9860.9870.9940.9941.0000.9990.9880.981
Unnamed: 151.0001.0001.0001.0001.0001.0000.9840.9850.9910.9770.9850.9860.9930.9910.9991.0000.9910.987
Unnamed: 161.0001.0001.0001.0001.0001.0000.9900.9960.9790.9810.9820.9890.9930.9930.9880.9911.0001.000
Unnamed: 171.0001.0001.0001.0001.0001.0000.9850.9850.9740.9810.9740.9810.9900.9870.9810.9871.0001.000
2024-03-14T11:14:04.651379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 5Unnamed: 14Unnamed: 16Unnamed: 17
Unnamed: 41.0000.9890.7520.8080.745
Unnamed: 50.9891.0000.7600.8160.745
Unnamed: 140.7520.7601.0000.8140.785
Unnamed: 160.8080.8160.8141.0000.913
Unnamed: 170.7450.7450.7850.9131.000
2024-03-14T11:14:04.747152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 5Unnamed: 14Unnamed: 16Unnamed: 17
Unnamed: 41.0000.9890.7520.8080.745
Unnamed: 50.9891.0000.7600.8160.745
Unnamed: 140.7520.7601.0000.8140.785
Unnamed: 160.8080.8160.8141.0000.913
Unnamed: 170.7450.7450.7850.9131.000

Missing values

2024-03-14T11:13:57.880817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:13:58.083537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-14T11:13:58.240503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

보급대상별 PC보급 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
0대분류중분류소분류보급코드2009<NA>2010<NA>2011<NA>2012<NA>2013<NA>2014<NA>2015.10월말<NA>
1<NA><NA><NA><NA>단체/개인수량단체/개인수량단체/개인수량단체/개인수량단체/개인수량단체/개인수량단체/개인수량
2>개인장애인시각장애인A1100757516161919333315151515
3<NA><NA>청각장애인A120020201111221515121255
4<NA><NA>지체장애인A130024124195954545134134113113103103
5<NA><NA>기타장애인A140077774848190190898951517070
6<NA>저소득층기초생활수급자A2100246246215215333333313313273273243243
7<NA><NA>차상위계층A2200191939394848555547475353
8<NA>소년소녀가장소년소녀가장A3100112200001111
9<NA>국가유공자(상이등급판정자)국가유공자(상이등급판정자)A41001010551414191921211313
보급대상별 PC보급 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
39<NA><NA>대안학교B82002100000151313
40<NA><NA>기타단체B83003017212601332124810271249
41<NA><NA>마을회관B8400000035111300
42<NA>해외정부기관B9100000000000000
43<NA><NA>NGOB9200000000000000
44<NA><NA>재외공관B9300000000000000
45<NA><NA>학교시설B9400000000000000
46<NA><NA>기타B9900000000000000
47<NA>소계<NA><NA>0024015262379071965291013318321672263
48합계<NA><NA><NA>0010682354787145790212359591189811944643834