Overview

Dataset statistics

Number of variables7
Number of observations863
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.7 KiB
Average record size in memory60.2 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description2020년부터 2022년까지 개인정보 보호 영향평가를 실시한 공공기관에 대한 데이터로 대상기관과 평가대상 시스템명 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15119841/fileData.do

Alerts

순번 is highly overall correlated with 년도High correlation
년도 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:41:14.157037
Analysis finished2023-12-12 15:41:16.352664
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct863
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean432
Minimum1
Maximum863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-13T00:41:16.483571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44.1
Q1216.5
median432
Q3647.5
95-th percentile819.9
Maximum863
Range862
Interquartile range (IQR)431

Descriptive statistics

Standard deviation249.27094
Coefficient of variation (CV)0.57701606
Kurtosis-1.2
Mean432
Median Absolute Deviation (MAD)216
Skewness0
Sum372816
Variance62136
MonotonicityStrictly increasing
2023-12-13T00:41:16.704285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
581 1
 
0.1%
570 1
 
0.1%
571 1
 
0.1%
572 1
 
0.1%
573 1
 
0.1%
574 1
 
0.1%
575 1
 
0.1%
576 1
 
0.1%
577 1
 
0.1%
Other values (853) 853
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
863 1
0.1%
862 1
0.1%
861 1
0.1%
860 1
0.1%
859 1
0.1%
858 1
0.1%
857 1
0.1%
856 1
0.1%
855 1
0.1%
854 1
0.1%

년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2021
320 
2022
273 
2020
270 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2021 320
37.1%
2022 273
31.6%
2020 270
31.3%

Length

2023-12-13T00:41:16.907321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:41:17.034848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 320
37.1%
2022 273
31.6%
2020 270
31.3%

대상기관
Text

Distinct315
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2023-12-13T00:41:17.300807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length6.3592121
Min length2

Characters and Unicode

Total characters5488
Distinct characters223
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)19.8%

Sample

1st row신용보증기금
2nd row신용보증기금
3rd row도로교통공단
4th row디지털서울문화예술대학교
5th row제주특별자치도
ValueCountFrequency (%)
한국사회보장정보원 32
 
3.7%
국민연금공단 32
 
3.7%
행정안전부 25
 
2.9%
건강보험심사평가원 22
 
2.5%
서울특별시 16
 
1.8%
국민건강보험공단 16
 
1.8%
중소기업은행 14
 
1.6%
국토교통부 13
 
1.5%
한국교통안전공단 13
 
1.5%
근로복지공단 12
 
1.4%
Other values (304) 672
77.5%
2023-12-13T00:41:17.793661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 342
 
6.2%
원 241
 
4.4%
한 225
 
4.1%
공 194
 
3.5%
보 178
 
3.2%
단 140
 
2.6%
사 132
 
2.4%
시 132
 
2.4%
교 128
 
2.3%
정 107
 
1.9%
Other values (213) 3669
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5443
99.2%
Space Separator 13
 
0.2%
Open Punctuation 12
 
0.2%
Close Punctuation 12
 
0.2%
Uppercase Letter 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 342
 
6.3%
원 241
 
4.4%
한 225
 
4.1%
공 194
 
3.6%
보 178
 
3.3%
단 140
 
2.6%
사 132
 
2.4%
시 132
 
2.4%
교 128
 
2.4%
정 107
 
2.0%
Other values (203) 3624
66.6%
Uppercase Letter
ValueCountFrequency (%)
I 1
16.7%
S 1
16.7%
K 1
16.7%
E 1
16.7%
T 1
16.7%
P 1
16.7%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5443
99.2%
Common 39
 
0.7%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 342
 
6.3%
원 241
 
4.4%
한 225
 
4.1%
공 194
 
3.6%
보 178
 
3.3%
단 140
 
2.6%
사 132
 
2.4%
시 132
 
2.4%
교 128
 
2.4%
정 107
 
2.0%
Other values (203) 3624
66.6%
Latin
ValueCountFrequency (%)
I 1
16.7%
S 1
16.7%
K 1
16.7%
E 1
16.7%
T 1
16.7%
P 1
16.7%
Common
ValueCountFrequency (%)
13
33.3%
( 12
30.8%
) 12
30.8%
. 2
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5443
99.2%
ASCII 45
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 342
 
6.3%
원 241
 
4.4%
한 225
 
4.1%
공 194
 
3.6%
보 178
 
3.3%
단 140
 
2.6%
사 132
 
2.4%
시 132
 
2.4%
교 128
 
2.4%
정 107
 
2.0%
Other values (203) 3624
66.6%
ASCII
ValueCountFrequency (%)
13
28.9%
( 12
26.7%
) 12
26.7%
. 2
 
4.4%
I 1
 
2.2%
S 1
 
2.2%
K 1
 
2.2%
E 1
 
2.2%
T 1
 
2.2%
P 1
 
2.2%

평가대상 시스템명
Text

Distinct671
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2023-12-13T00:41:18.123254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length23
Mean length11.748552
Min length3

Characters and Unicode

Total characters10139
Distinct characters446
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique594 ?
Unique (%)68.8%

Sample

1st row비대면 신용보증 플랫폼
2nd row매출채권보험 플랫폼
3rd row긴급자동차 자체교육 이수자 업로드시스템
4th row학사관리시스템
5th row제주형 재난긴급생활지원금 시스템
ValueCountFrequency (%)
시스템 74
 
4.8%
차세대 36
 
2.3%
연금업무시스템 22
 
1.4%
플랫폼 21
 
1.4%
홈페이지 20
 
1.3%
표준지방세정보시스템 17
 
1.1%
및 16
 
1.0%
병원정보시스템(medios 14
 
0.9%
모바일 13
 
0.8%
정보시스템 13
 
0.8%
Other values (958) 1286
83.9%
2023-12-13T00:41:18.546056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 757
 
7.5%
시 737
 
7.3%
템 702
 
6.9%
690
 
6.8%
정 298
 
2.9%
보 282
 
2.8%
지 212
 
2.1%
리 184
 
1.8%
관 179
 
1.8%
합 158
 
1.6%
Other values (436) 5940
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8679
85.6%
Space Separator 690
 
6.8%
Uppercase Letter 348
 
3.4%
Lowercase Letter 135
 
1.3%
Open Punctuation 88
 
0.9%
Close Punctuation 81
 
0.8%
Decimal Number 54
 
0.5%
Dash Punctuation 28
 
0.3%
Other Punctuation 18
 
0.2%
Math Symbol 17
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 757
 
8.7%
시 737
 
8.5%
템 702
 
8.1%
정 298
 
3.4%
보 282
 
3.2%
지 212
 
2.4%
리 184
 
2.1%
관 179
 
2.1%
합 158
 
1.8%
통 142
 
1.6%
Other values (378) 5028
57.9%
Uppercase Letter
ValueCountFrequency (%)
I 42
12.1%
S 40
11.5%
M 28
 
8.0%
A 27
 
7.8%
R 24
 
6.9%
D 23
 
6.6%
C 23
 
6.6%
O 20
 
5.7%
K 20
 
5.7%
T 18
 
5.2%
Other values (12) 83
23.9%
Lowercase Letter
ValueCountFrequency (%)
e 33
24.4%
i 25
18.5%
o 17
12.6%
s 16
11.9%
d 15
11.1%
t 5
 
3.7%
a 5
 
3.7%
n 4
 
3.0%
p 3
 
2.2%
r 3
 
2.2%
Other values (7) 9
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 13
24.1%
1 12
22.2%
4 7
13.0%
0 7
13.0%
3 6
11.1%
9 4
 
7.4%
5 2
 
3.7%
8 2
 
3.7%
6 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 10
55.6%
· 4
 
22.2%
& 3
 
16.7%
. 1
 
5.6%
Space Separator
ValueCountFrequency (%)
690
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
+ 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8679
85.6%
Common 977
 
9.6%
Latin 483
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 757
 
8.7%
시 737
 
8.5%
템 702
 
8.1%
정 298
 
3.4%
보 282
 
3.2%
지 212
 
2.4%
리 184
 
2.1%
관 179
 
2.1%
합 158
 
1.8%
통 142
 
1.6%
Other values (378) 5028
57.9%
Latin
ValueCountFrequency (%)
I 42
 
8.7%
S 40
 
8.3%
e 33
 
6.8%
M 28
 
5.8%
A 27
 
5.6%
i 25
 
5.2%
R 24
 
5.0%
D 23
 
4.8%
C 23
 
4.8%
O 20
 
4.1%
Other values (29) 198
41.0%
Common
ValueCountFrequency (%)
690
70.6%
( 88
 
9.0%
) 81
 
8.3%
- 28
 
2.9%
+ 17
 
1.7%
2 13
 
1.3%
1 12
 
1.2%
, 10
 
1.0%
4 7
 
0.7%
0 7
 
0.7%
Other values (9) 24
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8678
85.6%
ASCII 1456
 
14.4%
None 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 757
 
8.7%
시 737
 
8.5%
템 702
 
8.1%
정 298
 
3.4%
보 282
 
3.2%
지 212
 
2.4%
리 184
 
2.1%
관 179
 
2.1%
합 158
 
1.8%
통 142
 
1.6%
Other values (377) 5027
57.9%
ASCII
ValueCountFrequency (%)
690
47.4%
( 88
 
6.0%
) 81
 
5.6%
I 42
 
2.9%
S 40
 
2.7%
e 33
 
2.3%
M 28
 
1.9%
- 28
 
1.9%
A 27
 
1.9%
i 25
 
1.7%
Other values (47) 374
25.7%
None
ValueCountFrequency (%)
· 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

주소
Text

Distinct304
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2023-12-13T00:41:18.857113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length15.482039
Min length9

Characters and Unicode

Total characters13361
Distinct characters234
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

Unique167 ?
Unique (%)19.4%

Sample

1st row대구 동구 첨단로 7
2nd row대구 동구 첨단로 7
3rd row강원특별자치도 원주시 혁신로 2
4th row서울 서대문구 통일로37길 60
5th row제주 제주시 문연로 6
ValueCountFrequency (%)
서울 186
 
5.2%
중구 78
 
2.2%
세종 61
 
1.7%
동구 54
 
1.5%
강원 54
 
1.5%
경기 50
 
1.4%
원주시 50
 
1.4%
서구 49
 
1.4%
도움6로 44
 
1.2%
대구 41
 
1.2%
Other values (622) 2895
81.3%
2023-12-13T00:41:19.338832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2703
 
20.2%
로 853
 
6.4%
구 583
 
4.4%
1 445
 
3.3%
시 429
 
3.2%
2 340
 
2.5%
서 335
 
2.5%
0 320
 
2.4%
대 252
 
1.9%
4 247
 
1.8%
Other values (224) 6854
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8210
61.4%
Space Separator 2703
 
20.2%
Decimal Number 2397
 
17.9%
Dash Punctuation 33
 
0.2%
Other Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 853
 
10.4%
구 583
 
7.1%
시 429
 
5.2%
서 335
 
4.1%
대 252
 
3.1%
울 240
 
2.9%
주 204
 
2.5%
원 197
 
2.4%
종 178
 
2.2%
도 167
 
2.0%
Other values (211) 4772
58.1%
Decimal Number
ValueCountFrequency (%)
1 445
18.6%
2 340
14.2%
0 320
13.4%
4 247
10.3%
3 219
9.1%
6 196
8.2%
8 195
8.1%
5 156
 
6.5%
7 144
 
6.0%
9 135
 
5.6%
Space Separator
ValueCountFrequency (%)
2703
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Punctuation
ValueCountFrequency (%)
? 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8210
61.4%
Common 5151
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 853
 
10.4%
구 583
 
7.1%
시 429
 
5.2%
서 335
 
4.1%
대 252
 
3.1%
울 240
 
2.9%
주 204
 
2.5%
원 197
 
2.4%
종 178
 
2.2%
도 167
 
2.0%
Other values (211) 4772
58.1%
Common
ValueCountFrequency (%)
2703
52.5%
1 445
 
8.6%
2 340
 
6.6%
0 320
 
6.2%
4 247
 
4.8%
3 219
 
4.3%
6 196
 
3.8%
8 195
 
3.8%
5 156
 
3.0%
7 144
 
2.8%
Other values (3) 186
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8210
61.4%
ASCII 5151
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2703
52.5%
1 445
 
8.6%
2 340
 
6.6%
0 320
 
6.2%
4 247
 
4.8%
3 219
 
4.3%
6 196
 
3.8%
8 195
 
3.8%
5 156
 
3.0%
7 144
 
2.8%
Other values (3) 186
 
3.6%
Hangul
ValueCountFrequency (%)
로 853
 
10.4%
구 583
 
7.1%
시 429
 
5.2%
서 335
 
4.1%
대 252
 
3.1%
울 240
 
2.9%
주 204
 
2.5%
원 197
 
2.4%
종 178
 
2.2%
도 167
 
2.0%
Other values (211) 4772
58.1%

위도
Real number (ℝ)

Distinct290
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.674134
Minimum33.25321
Maximum38.14676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-13T00:41:19.493190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.25321
5-th percentile35.141946
Q135.97203
median36.78462
Q337.508845
95-th percentile37.578987
Maximum38.14676
Range4.89355
Interquartile range (IQR)1.536815

Descriptive statistics

Standard deviation0.95317087
Coefficient of variation (CV)0.025990277
Kurtosis1.1527381
Mean36.674134
Median Absolute Deviation (MAD)0.72651
Skewness-1.0874276
Sum31649.777
Variance0.90853472
MonotonicityNot monotonic
2023-12-13T00:41:19.652909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56499 34
 
3.9%
36.36225 34
 
3.9%
35.83886 32
 
3.7%
36.50341 31
 
3.6%
37.32299 22
 
2.5%
37.32468 16
 
1.9%
37.56635 16
 
1.9%
37.48411 14
 
1.6%
36.12468 13
 
1.5%
36.50594 13
 
1.5%
Other values (280) 638
73.9%
ValueCountFrequency (%)
33.25321 1
 
0.1%
33.4692 1
 
0.1%
33.47036 4
0.5%
33.48954 4
0.5%
33.4897 1
 
0.1%
33.49958 2
 
0.2%
33.51037 8
0.9%
34.51236 1
 
0.1%
34.80353 1
 
0.1%
34.8175 1
 
0.1%
ValueCountFrequency (%)
38.14676 7
0.8%
37.88396 1
 
0.1%
37.88065 1
 
0.1%
37.868 1
 
0.1%
37.8344 1
 
0.1%
37.81026 1
 
0.1%
37.78787 6
0.7%
37.77452 1
 
0.1%
37.76872 1
 
0.1%
37.74955 1
 
0.1%

경도
Real number (ℝ)

Distinct289
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.47018
Minimum126.29977
Maximum129.39686
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-13T00:41:19.822314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.29977
5-th percentile126.64945
Q1126.97831
median127.26117
Q3127.97964
95-th percentile129.06585
Maximum129.39686
Range3.09709
Interquartile range (IQR)1.00133

Descriptive statistics

Standard deviation0.74242203
Coefficient of variation (CV)0.0058242803
Kurtosis0.16219122
Mean127.47018
Median Absolute Deviation (MAD)0.2883
Skewness1.111357
Sum110006.76
Variance0.55119047
MonotonicityNot monotonic
2023-12-13T00:41:19.988503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.08444 34
 
3.9%
127.38494 34
 
3.9%
127.06685 32
 
3.7%
127.26537 31
 
3.6%
127.98071 22
 
2.5%
127.9863 16
 
1.9%
126.97831 16
 
1.9%
126.65506 14
 
1.6%
128.18365 13
 
1.5%
127.26267 13
 
1.5%
Other values (279) 638
73.9%
ValueCountFrequency (%)
126.29977 2
 
0.2%
126.40585 1
 
0.1%
126.43527 5
0.6%
126.46542 1
 
0.1%
126.46575 1
 
0.1%
126.46619 1
 
0.1%
126.47397 1
 
0.1%
126.49819 4
0.5%
126.5004 1
 
0.1%
126.51961 1
 
0.1%
ValueCountFrequency (%)
129.39686 1
 
0.1%
129.36509 3
 
0.3%
129.32692 1
 
0.1%
129.31428 12
1.4%
129.31381 7
0.8%
129.31377 2
 
0.2%
129.22484 3
 
0.3%
129.16314 3
 
0.3%
129.1259 3
 
0.3%
129.10378 2
 
0.2%

Interactions

2023-12-13T00:41:15.685963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:14.901026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.302402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.835115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.026457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.433089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.967676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.155338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:41:15.557919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:41:20.087412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번년도위도경도
순번1.0000.9620.3150.427
년도0.9621.0000.2610.220
위도0.3150.2611.0000.859
경도0.4270.2200.8591.000
2023-12-13T00:41:20.497465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도년도
순번1.0000.035-0.0000.959
위도0.0351.000-0.4070.118
경도-0.000-0.4071.0000.134
년도0.9590.1180.1341.000

Missing values

2023-12-13T00:41:16.127233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:41:16.288696image/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.

Sample

순번년도대상기관평가대상 시스템명주소위도경도
012020신용보증기금비대면 신용보증 플랫폼대구 동구 첨단로 735.88159128.73116
122020신용보증기금매출채권보험 플랫폼대구 동구 첨단로 735.88159128.73116
232020도로교통공단긴급자동차 자체교육 이수자 업로드시스템강원특별자치도 원주시 혁신로 237.3245127.97536
342020디지털서울문화예술대학교학사관리시스템서울 서대문구 통일로37길 6037.58714126.94385
452020제주특별자치도제주형 재난긴급생활지원금 시스템제주 제주시 문연로 633.48954126.49819
562020한국출판문화산업진흥원인문정신문화 온라인서비스 제공전북 전주시 덕진구 중동로 6335.84429127.06281
672020광주광역시지방경찰청교통단속관리시스템광주 광산구 용아로 11235.15373126.80053
782020한국의약품안전관리원마약류통합관리시스템경기 안양시 동안구 부림로169번길 3037.39781126.96095
892020한국산업안전보건공단어울림시스템울산 중구 종가로 40035.5647129.31381
9102020한국의약품안전관리원의료용 마약류 빅데이터 활용서비스경기 안양시 동안구 부림로169번길 3037.39781126.96095
순번년도대상기관평가대상 시스템명주소위도경도
8538542022산림청산림기술정보통합관리시스템대전광역시 서구 청사로 18936.36225127.38494
8548552022인천광역시표준세외수입정보시스템인천 남동구 정각로 2937.45593126.70627
8558562022인천광역시지방재정관리시스템(e호조)인천 남동구 정각로 2937.45593126.70627
8568572022대구광역시수용가정보시스템대구광역시 중구 공평로 8835.87184128.60086
8578582022여성가족부아이돌봄 통합업무 관리시스템서울 종로구 세종대로 20937.57509126.97486
8588592022인천광역시정비사업 추정분담금 정보시스템인천 남동구 정각로 2937.45593126.70627
8598602022여성가족부청소년활동통합관리시스템서울 종로구 세종대로 20937.57509126.97486
8608612022여성가족부e새일 시스템서울 종로구 세종대로 20937.57509126.97486
8618622022여성가족부성범죄자 신상정보 공개시스템서울 종로구 세종대로 20937.57509126.97486
8628632022여성가족부위민넷 시스템서울 종로구 세종대로 20937.57509126.97486