Overview

Dataset statistics

Number of variables11
Number of observations300
Missing cells1738
Missing cells (%)52.7%
Duplicate rows12
Duplicate rows (%)4.0%
Total size in memory25.9 KiB
Average record size in memory88.4 B

Variable types

Text7
Unsupported2
Categorical2

Dataset

Description서울특별시 소재 노인 요양시설의 일회용 기저귀 처리 현황과 관련한 데이터로 시설명, 주소, 처리방법 등의 정보를 제공합니다.
Author서울특별시
URLhttps://www.data.go.kr/data/15099589/fileData.do

Alerts

Unnamed: 10 has constant value ""Constant
Dataset has 12 (4.0%) duplicate rowsDuplicates
Unnamed: 4 is highly overall correlated with Unnamed: 7High correlation
Unnamed: 7 is highly overall correlated with Unnamed: 4High correlation
Unnamed: 7 is highly imbalanced (55.0%)Imbalance
Unnamed: 0 has 297 (99.0%) missing valuesMissing
Unnamed: 1 has 273 (91.0%) missing valuesMissing
Unnamed: 2 has 89 (29.7%) missing valuesMissing
Unnamed: 3 has 92 (30.7%) missing valuesMissing
Unnamed: 5 has 69 (23.0%) missing valuesMissing
Unnamed: 6 has 71 (23.7%) missing valuesMissing
Unnamed: 8 has 274 (91.3%) missing valuesMissing
Unnamed: 9 has 274 (91.3%) missing valuesMissing
Unnamed: 10 has 299 (99.7%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 14:51:12.297987
Analysis finished2023-12-12 14:51:13.664451
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing297
Missing (%)99.0%
Memory size2.5 KiB
2023-12-12T23:51:13.723306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6666667
Min length2

Characters and Unicode

Total characters8
Distinct characters5
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

Unique1 ?
Unique (%)33.3%

Sample

1st row시도
2nd row서울
3rd row서울
ValueCountFrequency (%)
서울 2
66.7%
시도 1
33.3%
2023-12-12T23:51:13.999406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 2
25.0%
울 2
25.0%
2
25.0%
시 1
12.5%
도 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
75.0%
Space Separator 2
 
25.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2
33.3%
울 2
33.3%
시 1
16.7%
도 1
16.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
75.0%
Common 2
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2
33.3%
울 2
33.3%
시 1
16.7%
도 1
16.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
75.0%
ASCII 2
 
25.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 2
33.3%
울 2
33.3%
시 1
16.7%
도 1
16.7%
ASCII
ValueCountFrequency (%)
2
100.0%

Unnamed: 1
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing273
Missing (%)91.0%
Memory size2.5 KiB
2023-12-12T23:51:14.224232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length1

Characters and Unicode

Total characters81
Distinct characters39
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

Unique27 ?
Unique (%)100.0%

Sample

1st row시군구
2nd row계
3rd row종로구
4th row중구
5th row용산구
ValueCountFrequency (%)
시군구 1
 
3.7%
서대문구 1
 
3.7%
송파구 1
 
3.7%
강남구 1
 
3.7%
서초구 1
 
3.7%
관악구 1
 
3.7%
동작구 1
 
3.7%
영등포구 1
 
3.7%
금천구 1
 
3.7%
구로구 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T23:51:14.699880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 27
33.3%
동 4
 
4.9%
강 4
 
4.9%
서 3
 
3.7%
북 2
 
2.5%
포 2
 
2.5%
로 2
 
2.5%
중 2
 
2.5%
천 2
 
2.5%
성 2
 
2.5%
Other values (29) 31
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 27
33.3%
동 4
 
4.9%
강 4
 
4.9%
서 3
 
3.7%
북 2
 
2.5%
포 2
 
2.5%
로 2
 
2.5%
중 2
 
2.5%
천 2
 
2.5%
성 2
 
2.5%
Other values (29) 31
38.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 27
33.3%
동 4
 
4.9%
강 4
 
4.9%
서 3
 
3.7%
북 2
 
2.5%
포 2
 
2.5%
로 2
 
2.5%
중 2
 
2.5%
천 2
 
2.5%
성 2
 
2.5%
Other values (29) 31
38.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 27
33.3%
동 4
 
4.9%
강 4
 
4.9%
서 3
 
3.7%
북 2
 
2.5%
포 2
 
2.5%
로 2
 
2.5%
중 2
 
2.5%
천 2
 
2.5%
성 2
 
2.5%
Other values (29) 31
38.3%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing89
Missing (%)29.7%
Memory size2.5 KiB

Unnamed: 3
Text

MISSING 

Distinct205
Distinct (%)98.6%
Missing92
Missing (%)30.7%
Memory size2.5 KiB
2023-12-12T23:51:15.103154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length16.990385
Min length2

Characters and Unicode

Total characters3534
Distinct characters224
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)97.1%

Sample

1st row주소
2nd row종로구 비봉길 76(구기동)
3rd row종로구 홍지문길 29(홍지동)
4th row종로구 평창동 553-5
5th row종로구 평창2길 5(평창동)
ValueCountFrequency (%)
도봉구 23
 
3.2%
강서구 17
 
2.4%
강북구 14
 
1.9%
은평구 13
 
1.8%
양천구 11
 
1.5%
서대문구 11
 
1.5%
성북구 10
 
1.4%
광진구 10
 
1.4%
금천구 10
 
1.4%
강동구 7
 
1.0%
Other values (439) 593
82.5%
2023-12-12T23:51:15.730638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
527
 
14.9%
로 199
 
5.6%
구 183
 
5.2%
1 158
 
4.5%
동 150
 
4.2%
( 114
 
3.2%
) 114
 
3.2%
2 109
 
3.1%
길 105
 
3.0%
3 102
 
2.9%
Other values (214) 1773
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1860
52.6%
Decimal Number 822
23.3%
Space Separator 527
 
14.9%
Open Punctuation 115
 
3.3%
Close Punctuation 115
 
3.3%
Other Punctuation 57
 
1.6%
Dash Punctuation 37
 
1.0%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 199
 
10.7%
구 183
 
9.8%
동 150
 
8.1%
길 105
 
5.6%
서 50
 
2.7%
강 47
 
2.5%
봉 46
 
2.5%
도 43
 
2.3%
천 39
 
2.1%
층 37
 
2.0%
Other values (195) 961
51.7%
Decimal Number
ValueCountFrequency (%)
1 158
19.2%
2 109
13.3%
3 102
12.4%
4 91
11.1%
5 87
10.6%
6 72
8.8%
0 56
 
6.8%
7 54
 
6.6%
8 49
 
6.0%
9 44
 
5.4%
Open Punctuation
ValueCountFrequency (%)
( 114
99.1%
[ 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 114
99.1%
] 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 54
94.7%
. 3
 
5.3%
Space Separator
ValueCountFrequency (%)
527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1860
52.6%
Common 1674
47.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 199
 
10.7%
구 183
 
9.8%
동 150
 
8.1%
길 105
 
5.6%
서 50
 
2.7%
강 47
 
2.5%
봉 46
 
2.5%
도 43
 
2.3%
천 39
 
2.1%
층 37
 
2.0%
Other values (195) 961
51.7%
Common
ValueCountFrequency (%)
527
31.5%
1 158
 
9.4%
( 114
 
6.8%
) 114
 
6.8%
2 109
 
6.5%
3 102
 
6.1%
4 91
 
5.4%
5 87
 
5.2%
6 72
 
4.3%
0 56
 
3.3%
Other values (9) 244
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1860
52.6%
ASCII 1674
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
527
31.5%
1 158
 
9.4%
( 114
 
6.8%
) 114
 
6.8%
2 109
 
6.5%
3 102
 
6.1%
4 91
 
5.4%
5 87
 
5.2%
6 72
 
4.3%
0 56
 
3.3%
Other values (9) 244
14.6%
Hangul
ValueCountFrequency (%)
로 199
 
10.7%
구 183
 
9.8%
동 150
 
8.1%
길 105
 
5.6%
서 50
 
2.7%
강 47
 
2.5%
봉 46
 
2.5%
도 43
 
2.3%
천 39
 
2.1%
층 37
 
2.0%
Other values (195) 961
51.7%

Unnamed: 4
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
종량제
96 
<NA>
91 
도시환경㈜
35 
㈜메디코, ㈜엔비텍코리아
11 
㈜삼우그린
10 
Other values (29)
57 

Length

Max length25
Median length13
Mean length4.4066667
Min length2

Unique

Unique23 ?
Unique (%)7.7%

Sample

1st row<NA>
2nd row일회용기저귀 처리방법
3rd row시군구 또는 처리업체 위탁 (처리업체명 기재)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
종량제 96
32.0%
<NA> 91
30.3%
도시환경㈜ 35
 
11.7%
㈜메디코, ㈜엔비텍코리아 11
 
3.7%
㈜삼우그린 10
 
3.3%
다솜 9
 
3.0%
㈜메디코 8
 
2.7%
(주)삼우그린 6
 
2.0%
㈜ 삼우그린 5
 
1.7%
복산상사 3
 
1.0%
Other values (24) 26
 
8.7%

Length

2023-12-12T23:51:15.929234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종량제 96
29.5%
na 91
28.0%
도시환경㈜ 35
 
10.8%
㈜메디코 19
 
5.8%
㈜엔비텍코리아 12
 
3.7%
㈜삼우그린 10
 
3.1%
다솜 9
 
2.8%
주)삼우그린 6
 
1.8%
㈜ 6
 
1.8%
삼우그린 5
 
1.5%
Other values (31) 36
 
11.1%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)23.0%
Memory size2.5 KiB

Unnamed: 6
Text

MISSING 

Distinct191
Distinct (%)83.4%
Missing71
Missing (%)23.7%
Memory size2.5 KiB
2023-12-12T23:51:16.259204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length28
Mean length18.803493
Min length2

Characters and Unicode

Total characters4306
Distinct characters191
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)70.3%

Sample

1st row주소
2nd row창경궁로16길 32(연지동)
3rd row종로구 자하문로28길 29(청운동)
4th row중구 청구로17길 98
5th row용산구 효창원로 15길 24
ValueCountFrequency (%)
도봉구 38
 
4.3%
강동구 21
 
2.4%
3층 18
 
2.0%
양천구 18
 
2.0%
2층 18
 
2.0%
5층 17
 
1.9%
방학동 17
 
1.9%
4층 17
 
1.9%
금천구 13
 
1.5%
광진구 12
 
1.4%
Other values (372) 695
78.6%
2023-12-12T23:51:16.850134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
685
 
15.9%
로 226
 
5.2%
동 181
 
4.2%
1 170
 
3.9%
구 168
 
3.9%
, 157
 
3.6%
2 156
 
3.6%
( 145
 
3.4%
) 144
 
3.3%
층 132
 
3.1%
Other values (181) 2142
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2143
49.8%
Decimal Number 995
23.1%
Space Separator 685
 
15.9%
Other Punctuation 159
 
3.7%
Open Punctuation 146
 
3.4%
Close Punctuation 145
 
3.4%
Dash Punctuation 29
 
0.7%
Math Symbol 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 226
 
10.5%
동 181
 
8.4%
구 168
 
7.8%
층 132
 
6.2%
길 84
 
3.9%
봉 65
 
3.0%
도 62
 
2.9%
빌 50
 
2.3%
딩 49
 
2.3%
천 47
 
2.2%
Other values (160) 1079
50.3%
Decimal Number
ValueCountFrequency (%)
1 170
17.1%
2 156
15.7%
4 132
13.3%
3 124
12.5%
5 88
8.8%
6 83
8.3%
7 77
7.7%
9 64
 
6.4%
0 59
 
5.9%
8 42
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 157
98.7%
/ 2
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 145
99.3%
[ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 144
99.3%
] 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
685
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2161
50.2%
Hangul 2143
49.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 226
 
10.5%
동 181
 
8.4%
구 168
 
7.8%
층 132
 
6.2%
길 84
 
3.9%
봉 65
 
3.0%
도 62
 
2.9%
빌 50
 
2.3%
딩 49
 
2.3%
천 47
 
2.2%
Other values (160) 1079
50.3%
Common
ValueCountFrequency (%)
685
31.7%
1 170
 
7.9%
, 157
 
7.3%
2 156
 
7.2%
( 145
 
6.7%
) 144
 
6.7%
4 132
 
6.1%
3 124
 
5.7%
5 88
 
4.1%
6 83
 
3.8%
Other values (9) 277
12.8%
Latin
ValueCountFrequency (%)
D 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2163
50.2%
Hangul 2143
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
685
31.7%
1 170
 
7.9%
, 157
 
7.3%
2 156
 
7.2%
( 145
 
6.7%
) 144
 
6.7%
4 132
 
6.1%
3 124
 
5.7%
5 88
 
4.1%
6 83
 
3.8%
Other values (11) 279
12.9%
Hangul
ValueCountFrequency (%)
로 226
 
10.5%
동 181
 
8.4%
구 168
 
7.8%
층 132
 
6.2%
길 84
 
3.9%
봉 65
 
3.0%
도 62
 
2.9%
빌 50
 
2.3%
딩 49
 
2.3%
천 47
 
2.2%
Other values (160) 1079
50.3%

Unnamed: 7
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
종량제
189 
<NA>
70 
도시환경㈜
 
11
(주)삼우그린
 
10
㈜메디코,㈜엔비텍코리아
 
4
Other values (9)
 
16

Length

Max length25
Median length3
Mean length3.8133333
Min length3

Unique

Unique6 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row일회용기저귀 처리방법
3rd row시군구 또는 처리업체 위탁 (처리업체명 기재)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
종량제 189
63.0%
<NA> 70
 
23.3%
도시환경㈜ 11
 
3.7%
(주)삼우그린 10
 
3.3%
㈜메디코,㈜엔비텍코리아 4
 
1.3%
㈜ 삼우그린) 4
 
1.3%
㈜삼우그린 3
 
1.0%
프레벤 3
 
1.0%
일회용기저귀 처리방법 1
 
0.3%
시군구 또는 처리업체 위탁 (처리업체명 기재) 1
 
0.3%
Other values (4) 4
 
1.3%

Length

2023-12-12T23:51:17.034411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종량제 189
60.4%
na 70
 
22.4%
도시환경㈜ 11
 
3.5%
주)삼우그린 10
 
3.2%
㈜메디코,㈜엔비텍코리아 4
 
1.3%
㈜ 4
 
1.3%
삼우그린 4
 
1.3%
㈜삼우그린 3
 
1.0%
프레벤 3
 
1.0%
또는 2
 
0.6%
Other values (13) 13
 
4.2%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing274
Missing (%)91.3%
Memory size2.5 KiB
2023-12-12T23:51:17.270537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters78
Distinct characters49
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

Unique26 ?
Unique (%)100.0%

Sample

1st row담당자
2nd row김정숙
3rd row이지아
4th row이선경
5th row조성연
ValueCountFrequency (%)
박진영 1
 
3.8%
김정숙 1
 
3.8%
김기병 1
 
3.8%
김수영 1
 
3.8%
이석환 1
 
3.8%
황철구 1
 
3.8%
주영우 1
 
3.8%
김혜림 1
 
3.8%
강수나 1
 
3.8%
이원지 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T23:51:17.633077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
7.7%
영 5
 
6.4%
이 5
 
6.4%
박 3
 
3.8%
정 3
 
3.8%
현 2
 
2.6%
구 2
 
2.6%
우 2
 
2.6%
진 2
 
2.6%
수 2
 
2.6%
Other values (39) 46
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
7.7%
영 5
 
6.4%
이 5
 
6.4%
박 3
 
3.8%
정 3
 
3.8%
현 2
 
2.6%
구 2
 
2.6%
우 2
 
2.6%
진 2
 
2.6%
수 2
 
2.6%
Other values (39) 46
59.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
7.7%
영 5
 
6.4%
이 5
 
6.4%
박 3
 
3.8%
정 3
 
3.8%
현 2
 
2.6%
구 2
 
2.6%
우 2
 
2.6%
진 2
 
2.6%
수 2
 
2.6%
Other values (39) 46
59.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 6
 
7.7%
영 5
 
6.4%
이 5
 
6.4%
박 3
 
3.8%
정 3
 
3.8%
현 2
 
2.6%
구 2
 
2.6%
우 2
 
2.6%
진 2
 
2.6%
수 2
 
2.6%
Other values (39) 46
59.0%

Unnamed: 9
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing274
Missing (%)91.3%
Memory size2.5 KiB
2023-12-12T23:51:17.850320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.461538
Min length8

Characters and Unicode

Total characters298
Distinct characters19
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

Unique26 ?
Unique (%)100.0%

Sample

1st row연락처 (기재)
2nd row02-2148-2384
3rd row02-3396-5366
4th row02-2199-7114
5th row02-2286-5525
ValueCountFrequency (%)
351-7565 1
 
3.7%
기재 1
 
3.7%
02-330-1631 1
 
3.7%
02-2147-3257 1
 
3.7%
02-3423-5924 1
 
3.7%
02-2155-8872 1
 
3.7%
02-879-6161 1
 
3.7%
02-820-9632 1
 
3.7%
02-2670-3472 1
 
3.7%
02-2627-1393 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T23:51:18.282454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 60
20.1%
- 49
16.4%
0 37
12.4%
3 26
8.7%
5 23
 
7.7%
6 21
 
7.0%
1 20
 
6.7%
4 17
 
5.7%
7 14
 
4.7%
8 12
 
4.0%
Other values (9) 19
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 241
80.9%
Dash Punctuation 49
 
16.4%
Other Letter 5
 
1.7%
Control 1
 
0.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 60
24.9%
0 37
15.4%
3 26
10.8%
5 23
 
9.5%
6 21
 
8.7%
1 20
 
8.3%
4 17
 
7.1%
7 14
 
5.8%
8 12
 
5.0%
9 11
 
4.6%
Other Letter
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
기 1
20.0%
재 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 293
98.3%
Hangul 5
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 60
20.5%
- 49
16.7%
0 37
12.6%
3 26
8.9%
5 23
 
7.8%
6 21
 
7.2%
1 20
 
6.8%
4 17
 
5.8%
7 14
 
4.8%
8 12
 
4.1%
Other values (4) 14
 
4.8%
Hangul
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
기 1
20.0%
재 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 293
98.3%
Hangul 5
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 60
20.5%
- 49
16.7%
0 37
12.6%
3 26
8.9%
5 23
 
7.8%
6 21
 
7.2%
1 20
 
6.8%
4 17
 
5.8%
7 14
 
4.8%
8 12
 
4.1%
Other values (4) 14
 
4.8%
Hangul
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
기 1
20.0%
재 1
20.0%

Unnamed: 10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing299
Missing (%)99.7%
Memory size2.5 KiB
2023-12-12T23:51:18.468884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters24
Distinct characters20
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

Unique1 ?
Unique (%)100.0%

Sample

1st row비고 (서식과 다른 내용이 있을 경우 작성)
ValueCountFrequency (%)
비고 1
14.3%
서식과 1
14.3%
다른 1
14.3%
내용이 1
14.3%
있을 1
14.3%
경우 1
14.3%
작성 1
14.3%
2023-12-12T23:51:18.803683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
20.8%
비 1
 
4.2%
용 1
 
4.2%
성 1
 
4.2%
작 1
 
4.2%
우 1
 
4.2%
경 1
 
4.2%
을 1
 
4.2%
있 1
 
4.2%
이 1
 
4.2%
Other values (10) 10
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
66.7%
Space Separator 5
 
20.8%
Open Punctuation 1
 
4.2%
Control 1
 
4.2%
Close Punctuation 1
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
 
6.2%
용 1
 
6.2%
성 1
 
6.2%
작 1
 
6.2%
우 1
 
6.2%
경 1
 
6.2%
을 1
 
6.2%
있 1
 
6.2%
이 1
 
6.2%
내 1
 
6.2%
Other values (6) 6
37.5%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
66.7%
Common 8
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
 
6.2%
용 1
 
6.2%
성 1
 
6.2%
작 1
 
6.2%
우 1
 
6.2%
경 1
 
6.2%
을 1
 
6.2%
있 1
 
6.2%
이 1
 
6.2%
내 1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
5
62.5%
( 1
 
12.5%
1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
66.7%
ASCII 8
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
62.5%
( 1
 
12.5%
1
 
12.5%
) 1
 
12.5%
Hangul
ValueCountFrequency (%)
비 1
 
6.2%
용 1
 
6.2%
성 1
 
6.2%
작 1
 
6.2%
우 1
 
6.2%
경 1
 
6.2%
을 1
 
6.2%
있 1
 
6.2%
이 1
 
6.2%
내 1
 
6.2%
Other values (6) 6
37.5%

Correlations

2023-12-12T23:51:18.904898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 0Unnamed: 1Unnamed: 4Unnamed: 7Unnamed: 8Unnamed: 9
Unnamed: 01.0001.000NaNNaN0.0000.000
Unnamed: 11.0001.0001.0001.0001.0001.000
Unnamed: 4NaN1.0001.0000.8851.0001.000
Unnamed: 7NaN1.0000.8851.0001.0001.000
Unnamed: 80.0001.0001.0001.0001.0001.000
Unnamed: 90.0001.0001.0001.0001.0001.000
2023-12-12T23:51:19.028188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 7
Unnamed: 41.0000.517
Unnamed: 70.5171.000
2023-12-12T23:51:19.120977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 7
Unnamed: 41.0000.517
Unnamed: 70.5171.000

Missing values

2023-12-12T23:51:13.174591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:51:13.361499image/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.
2023-12-12T23:51:13.517184image/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

Unnamed: 0Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10
0시도시군구지정폐기물(의료폐기물) 처리계획 현황<NA><NA>NaN<NA><NA>담당자연락처 (기재)비고 (서식과 다른 내용이 있을 경우 작성)
1<NA><NA>노인요양시설(노인복지법 제34조제1항제1호 대상시설만 기재)<NA>일회용기저귀 처리방법노인요양공동생활가정(노인복지법 제34조제1항제2호 대상시설)<NA>일회용기저귀 처리방법<NA><NA><NA>
2<NA><NA>노인요양시설명주소시군구 또는 처리업체 위탁 (처리업체명 기재)노인요양공동생활가정주소시군구 또는 처리업체 위탁 (처리업체명 기재)<NA><NA><NA>
3<NA><NA>NaN<NA><NA>NaN<NA><NA><NA><NA><NA>
4서울계207<NA><NA>228<NA><NA><NA><NA><NA>
5서울종로구사회복지법인청운요양원종로구 비봉길 76(구기동)㈜메디코실버행복생활창경궁로16길 32(연지동)종량제김정숙02-2148-2384<NA>
6<NA><NA>종로시니어스타워종로구 홍지문길 29(홍지동)도시환경㈜청운실버센터종로구 자하문로28길 29(청운동)도시환경㈜<NA><NA><NA>
7<NA><NA>평창동시니어센터종로구 평창동 553-5도시환경㈜NaN<NA><NA><NA><NA><NA>
8<NA><NA>세검정실버홈종로구 평창2길 5(평창동)도시환경㈜NaN<NA><NA><NA><NA><NA>
9<NA><NA>서울여자간호대학교휴먼캐슬종로구 평창길 318(평창동)도시환경㈜NaN<NA><NA><NA><NA><NA>
Unnamed: 0Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10
290<NA><NA>NaN<NA><NA>한사랑실버센터2호강동구 양재대로 1494종량제<NA><NA><NA>
291<NA><NA>NaN<NA><NA>은혜요양원강동구 양재대로124길 41종량제<NA><NA><NA>
292<NA><NA>NaN<NA><NA>소망요양원 1호점강동구 동남로81길 8종량제<NA><NA><NA>
293<NA><NA>NaN<NA><NA>소망요양원 2호점강동구 동남로81길 8종량제<NA><NA><NA>
294<NA><NA>NaN<NA><NA>흰돌장기요양센터 1호점강동구 구천면로 323종량제<NA><NA><NA>
295<NA><NA>NaN<NA><NA>흰돌장기요양센터 2호점강동구 구천면로 323종량제<NA><NA><NA>
296<NA><NA>NaN<NA><NA>흰돌장기요양센터 3호점강동구 구천면로 323종량제<NA><NA><NA>
297<NA><NA>NaN<NA><NA>황금나무너싱홈강동구 고덕로27길 33-27종량제<NA><NA><NA>
298<NA><NA>NaN<NA><NA>강동천호실버센터 1호강동구 올림픽로 664종량제<NA><NA><NA>
299<NA><NA>NaN<NA><NA>강동천호실버센터 2호강동구 올림픽로 664종량제<NA><NA><NA>

Duplicate rows

Most frequently occurring

Unnamed: 0Unnamed: 1Unnamed: 3Unnamed: 4Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10# duplicates
9<NA><NA><NA><NA>망우로 171, 5층 (중화동)(주)삼우그린<NA><NA><NA>4
0<NA><NA><NA><NA>강동구 구천면로 323종량제<NA><NA><NA>3
3<NA><NA><NA><NA>강동구 양재대로124길 41종량제<NA><NA><NA>3
1<NA><NA><NA><NA>강동구 동남로81길 8종량제<NA><NA><NA>2
2<NA><NA><NA><NA>강동구 양재대로 1494종량제<NA><NA><NA>2
4<NA><NA><NA><NA>강동구 올림픽로 664종량제<NA><NA><NA>2
5<NA><NA><NA><NA>고산자로 476, 3층(제기동)종량제<NA><NA><NA>2
6<NA><NA><NA><NA>고산자로 476, 4층(제기동)종량제<NA><NA><NA>2
7<NA><NA><NA><NA>도봉구 도봉로 669, 501호 (방학동, 이정빌딩)종량제<NA><NA><NA>2
8<NA><NA><NA><NA>동일로 1550, 604호(상계동, 고려프라자빌딩)종량제<NA><NA><NA>2