Overview

Dataset statistics

Number of variables6
Number of observations33
Missing cells130
Missing cells (%)65.7%
Duplicate rows1
Duplicate rows (%)3.0%
Total size in memory1.7 KiB
Average record size in memory53.0 B

Variable types

Unsupported2
Text3
Categorical1

Dataset

Description가압장과 배수지 상황을 24시간 원격감시하여 이상상황 발생시 긴급 비상출동하여 신속하게 조치(2020년 1월~2022년 5월)
Author대전광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15081210/fileData.do

Alerts

Unnamed: 2 has constant value ""Constant
Unnamed: 3 has constant value ""Constant
Unnamed: 4 has constant value ""Constant
Dataset has 1 (3.0%) duplicate rowsDuplicates
Unnamed: 5 is highly imbalanced (75.4%)Imbalance
Unnamed: 0 has 33 (100.0%) missing valuesMissing
원격감시상황실 비상출동 현황 has 1 (3.0%) missing valuesMissing
Unnamed: 2 has 32 (97.0%) missing valuesMissing
Unnamed: 3 has 32 (97.0%) missing valuesMissing
Unnamed: 4 has 32 (97.0%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
원격감시상황실 비상출동 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 11:21:59.582104
Analysis finished2023-12-12 11:22:00.205380
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

원격감시상황실 비상출동 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.0%
Memory size396.0 B

Unnamed: 2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-12T20:22:00.257288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st row시간
ValueCountFrequency (%)
시간 1
100.0%
2023-12-12T20:22:01.135006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1
50.0%
간 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1
50.0%
간 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1
50.0%
간 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1
50.0%
간 1
50.0%

Unnamed: 3
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-12T20:22:01.339005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row출동차량
ValueCountFrequency (%)
출동차량 1
100.0%
2023-12-12T20:22:01.792804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
차 1
25.0%
량 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
차 1
25.0%
량 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
차 1
25.0%
량 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
차 1
25.0%
량 1
25.0%

Unnamed: 4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-12T20:22:02.072101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row출동인력
ValueCountFrequency (%)
출동인력 1
100.0%
2023-12-12T20:22:02.549546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
인 1
25.0%
력 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
인 1
25.0%
력 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
인 1
25.0%
력 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
출 1
25.0%
동 1
25.0%
인 1
25.0%
력 1
25.0%

Unnamed: 5
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
이상없음
31 
<NA>
 
1
사유 및 처리결과
 
1

Length

Max length9
Median length4
Mean length4.1515152
Min length4

Unique

Unique2 ?
Unique (%)6.1%

Sample

1st row<NA>
2nd row사유 및 처리결과
3rd row이상없음
4th row이상없음
5th row이상없음

Common Values

ValueCountFrequency (%)
이상없음 31
93.9%
<NA> 1
 
3.0%
사유 및 처리결과 1
 
3.0%

Length

2023-12-12T20:22:02.731184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:22:02.854468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이상없음 31
88.6%
na 1
 
2.9%
사유 1
 
2.9%
및 1
 
2.9%
처리결과 1
 
2.9%

Missing values

2023-12-12T20:21:59.773555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:21:59.909009image/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.
2023-12-12T20:22:00.082856image/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: 0원격감시상황실 비상출동 현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0<NA>NaN<NA><NA><NA><NA>
1<NA>년월일시간출동차량출동인력사유 및 처리결과
2<NA>2020-01-01 00:00:00<NA><NA><NA>이상없음
3<NA>2020-01-02 00:00:00<NA><NA><NA>이상없음
4<NA>2020-01-03 00:00:00<NA><NA><NA>이상없음
5<NA>2020-01-04 00:00:00<NA><NA><NA>이상없음
6<NA>2020-01-05 00:00:00<NA><NA><NA>이상없음
7<NA>2020-01-06 00:00:00<NA><NA><NA>이상없음
8<NA>2020-01-07 00:00:00<NA><NA><NA>이상없음
9<NA>2020-01-08 00:00:00<NA><NA><NA>이상없음
Unnamed: 0원격감시상황실 비상출동 현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
23<NA>2020-01-22 00:00:00<NA><NA><NA>이상없음
24<NA>2020-01-23 00:00:00<NA><NA><NA>이상없음
25<NA>2020-01-24 00:00:00<NA><NA><NA>이상없음
26<NA>2020-01-25 00:00:00<NA><NA><NA>이상없음
27<NA>2020-01-26 00:00:00<NA><NA><NA>이상없음
28<NA>2020-01-27 00:00:00<NA><NA><NA>이상없음
29<NA>2020-01-28 00:00:00<NA><NA><NA>이상없음
30<NA>2020-01-29 00:00:00<NA><NA><NA>이상없음
31<NA>2020-01-30 00:00:00<NA><NA><NA>이상없음
32<NA>2020-01-31 00:00:00<NA><NA><NA>이상없음

Duplicate rows

Most frequently occurring

Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5# duplicates
0<NA><NA><NA>이상없음31