Overview

Dataset statistics

Number of variables16
Number of observations3999
Missing cells52525
Missing cells (%)82.1%
Duplicate rows51
Duplicate rows (%)1.3%
Total size in memory546.9 KiB
Average record size in memory140.0 B

Variable types

Text2
DateTime2
Unsupported12

Dataset

Description경상북도 경주시_도로와지하시설물관리시스템 현황 상수시설, 저수조, 계량기, 변류, 스탠드파이프,급수관료,배수지,정수장,수압계,가압펌프장, 등등
Author경상북도 경주시
URLhttps://www.data.go.kr/data/15091163/fileData.do

Alerts

Dataset has 51 (1.3%) duplicate rowsDuplicates
구분 has 40 (1.0%) missing valuesMissing
관리번호 has 79 (2.0%) missing valuesMissing
설치일자 has 891 (22.3%) missing valuesMissing
복구일자 has 3527 (88.2%) missing valuesMissing
Unnamed: 4 has 3999 (100.0%) missing valuesMissing
Unnamed: 5 has 3999 (100.0%) missing valuesMissing
Unnamed: 6 has 3999 (100.0%) missing valuesMissing
Unnamed: 7 has 3999 (100.0%) missing valuesMissing
Unnamed: 8 has 3999 (100.0%) missing valuesMissing
Unnamed: 9 has 3999 (100.0%) missing valuesMissing
Unnamed: 10 has 3999 (100.0%) missing valuesMissing
Unnamed: 11 has 3999 (100.0%) missing valuesMissing
Unnamed: 12 has 3999 (100.0%) missing valuesMissing
Unnamed: 13 has 3999 (100.0%) missing valuesMissing
Unnamed: 14 has 3999 (100.0%) missing valuesMissing
Unnamed: 15 has 3999 (100.0%) missing valuesMissing
Unnamed: 4 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
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 12:24:25.674171
Analysis finished2023-12-12 12:24:26.599702
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

MISSING 

Distinct99
Distinct (%)2.5%
Missing40
Missing (%)1.0%
Memory size31.4 KiB
2023-12-12T21:24:26.767499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.6294519
Min length6

Characters and Unicode

Total characters34164
Distinct characters140
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

Unique40 ?
Unique (%)1.0%

Sample

1st row 가로등 현황
2nd row 가로등 현황
3rd row 가로등 현황
4th row 가로등 현황
5th row 가로등 현황
ValueCountFrequency (%)
현황 3958
48.4%
배전정보 515
 
6.3%
하수맨홀 215
 
2.6%
도로표지판 198
 
2.4%
하수관거정보 165
 
2.0%
횡단보도 140
 
1.7%
하수민원접수처리대장 139
 
1.7%
물받이 138
 
1.7%
하수연결관 134
 
1.6%
과속방지턱 131
 
1.6%
Other values (95) 2437
29.8%
2023-12-12T21:24:27.182137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8170
23.9%
현 3958
 
11.6%
황 3958
 
11.6%
수 1333
 
3.9%
보 1310
 
3.8%
정 1154
 
3.4%
하 794
 
2.3%
전 604
 
1.8%
배 590
 
1.7%
관 529
 
1.5%
Other values (130) 11764
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25994
76.1%
Space Separator 8170
 
23.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
현 3958
 
15.2%
황 3958
 
15.2%
수 1333
 
5.1%
보 1310
 
5.0%
정 1154
 
4.4%
하 794
 
3.1%
전 604
 
2.3%
배 590
 
2.3%
관 529
 
2.0%
지 464
 
1.8%
Other values (129) 11300
43.5%
Space Separator
ValueCountFrequency (%)
8170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25994
76.1%
Common 8170
 
23.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
현 3958
 
15.2%
황 3958
 
15.2%
수 1333
 
5.1%
보 1310
 
5.0%
정 1154
 
4.4%
하 794
 
3.1%
전 604
 
2.3%
배 590
 
2.3%
관 529
 
2.0%
지 464
 
1.8%
Other values (129) 11300
43.5%
Common
ValueCountFrequency (%)
8170
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25994
76.1%
ASCII 8170
 
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8170
100.0%
Hangul
ValueCountFrequency (%)
현 3958
 
15.2%
황 3958
 
15.2%
수 1333
 
5.1%
보 1310
 
5.0%
정 1154
 
4.4%
하 794
 
3.1%
전 604
 
2.3%
배 590
 
2.3%
관 529
 
2.0%
지 464
 
1.8%
Other values (129) 11300
43.5%

관리번호
Text

MISSING 

Distinct2905
Distinct (%)74.1%
Missing79
Missing (%)2.0%
Memory size31.4 KiB
2023-12-12T21:24:27.604921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2811224
Min length1

Characters and Unicode

Total characters24622
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2354 ?
Unique (%)60.1%

Sample

1st row171309
2nd row171310
3rd row171308
4th row171303
5th row171304
ValueCountFrequency (%)
120001 13
 
0.3%
100001 12
 
0.3%
100002 11
 
0.3%
120002 11
 
0.3%
650001 10
 
0.3%
120005 8
 
0.2%
185002 8
 
0.2%
120003 8
 
0.2%
620001 8
 
0.2%
100003 8
 
0.2%
Other values (2895) 3823
97.5%
2023-12-12T21:24:28.182657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7252
29.5%
1 4135
16.8%
2 2752
 
11.2%
3 2314
 
9.4%
6 1726
 
7.0%
9 1347
 
5.5%
4 1240
 
5.0%
5 1217
 
4.9%
7 1211
 
4.9%
8 1169
 
4.7%
Other values (16) 259
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24363
98.9%
Uppercase Letter 259
 
1.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 32
12.4%
W 25
9.7%
X 24
 
9.3%
P 21
 
8.1%
Q 19
 
7.3%
R 17
 
6.6%
Y 17
 
6.6%
F 15
 
5.8%
B 14
 
5.4%
H 14
 
5.4%
Other values (6) 61
23.6%
Decimal Number
ValueCountFrequency (%)
0 7252
29.8%
1 4135
17.0%
2 2752
 
11.3%
3 2314
 
9.5%
6 1726
 
7.1%
9 1347
 
5.5%
4 1240
 
5.1%
5 1217
 
5.0%
7 1211
 
5.0%
8 1169
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 24363
98.9%
Latin 259
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 32
12.4%
W 25
9.7%
X 24
 
9.3%
P 21
 
8.1%
Q 19
 
7.3%
R 17
 
6.6%
Y 17
 
6.6%
F 15
 
5.8%
B 14
 
5.4%
H 14
 
5.4%
Other values (6) 61
23.6%
Common
ValueCountFrequency (%)
0 7252
29.8%
1 4135
17.0%
2 2752
 
11.3%
3 2314
 
9.5%
6 1726
 
7.1%
9 1347
 
5.5%
4 1240
 
5.1%
5 1217
 
5.0%
7 1211
 
5.0%
8 1169
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7252
29.5%
1 4135
16.8%
2 2752
 
11.2%
3 2314
 
9.4%
6 1726
 
7.0%
9 1347
 
5.5%
4 1240
 
5.0%
5 1217
 
4.9%
7 1211
 
4.9%
8 1169
 
4.7%
Other values (16) 259
 
1.1%

설치일자
Date

MISSING 

Distinct417
Distinct (%)13.4%
Missing891
Missing (%)22.3%
Memory size31.4 KiB
Minimum1899-12-31 00:00:00
Maximum2060-01-01 00:00:00
2023-12-12T21:24:28.386584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:24:28.585783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

복구일자
Date

MISSING 

Distinct16
Distinct (%)3.4%
Missing3527
Missing (%)88.2%
Memory size31.4 KiB
Minimum1900-01-01 00:00:00
Maximum2020-05-20 00:00:00
2023-12-12T21:24:28.732985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:24:28.871225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Unnamed: 15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3999
Missing (%)100.0%
Memory size35.3 KiB

Correlations

2023-12-12T21:24:28.982372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분복구일자
구분1.0000.998
복구일자0.9981.000

Missing values

2023-12-12T21:24:26.087302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:24:26.322707image/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.
2023-12-12T21:24:26.511636image/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

구분관리번호설치일자복구일자Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
0가로등 현황1713092017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1가로등 현황1713102017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2가로등 현황1713082017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3가로등 현황1713032017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4가로등 현황1713042017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5가로등 현황1713072017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6가로등 현황1713052017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7가로등 현황1713062017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8가로등 현황1713112017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9가로등 현황1713022017-02-20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
구분관리번호설치일자복구일자Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
3989<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3990<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3991<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3992<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3993<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3994<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3995<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3996<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3997<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분관리번호설치일자복구일자# duplicates
50<NA><NA><NA><NA>40
0기타시설정보 현황100001<NA><NA>2
1기타시설정보 현황100002<NA><NA>2
2기타시설정보 현황100003<NA><NA>2
3기타시설정보 현황100004<NA><NA>2
4기타시설정보 현황120001<NA><NA>2
5배전정보 현황201346264<NA><NA>2
6배전정보 현황201346336<NA><NA>2
7배전정보 현황250182933<NA><NA>2
8배전정보 현황250572673<NA><NA>2