Overview

Dataset statistics

Number of variables15
Number of observations282
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.0 KiB
Average record size in memory134.5 B

Variable types

Text1
Numeric14

Dataset

Description경찰청 민원분야 치안고객만족도(관서별)(응답자 특성, 종합만족도, 전반적만족도, 요소만족도, 업무처리절차 및 과정, 담당자 응대태도, 서비스 품질, 시설 및 이용환경, 신속성, 지원성, 성실성, 청렴성, 전문성, 공정성, 편리성)
Author경찰청
URLhttps://www.data.go.kr/data/15064323/fileData.do

Alerts

종합만족도 is highly overall correlated with 전반적만족도 and 12 other fieldsHigh correlation
전반적만족도 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
요소만족도 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
업무처리절차 및 과정 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
담당자응대태도 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
서비스품질 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
시설 및 이용환경 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
신속성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
지원성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
성실성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
청렴성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
전문성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
공정성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
편리성 is highly overall correlated with 종합만족도 and 12 other fieldsHigh correlation
응답자특성 has unique valuesUnique

Reproduction

Analysis started2024-03-23 06:16:41.692295
Analysis finished2024-03-23 06:17:54.334554
Duration1 minute and 12.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

응답자특성
Text

UNIQUE 

Distinct282
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-03-23T06:17:54.979760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.0638298
Min length3

Characters and Unicode

Total characters1710
Distinct characters154
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

Unique282 ?
Unique (%)100.0%

Sample

1st row기타민원
2nd row수사민원
3rd row유실물
4th row총포화약
5th row교통민원
ValueCountFrequency (%)
기타민원 1
 
0.4%
아산경찰서 1
 
0.4%
예산경찰서 1
 
0.4%
홍성경찰서 1
 
0.4%
당진경찰서 1
 
0.4%
보령경찰서 1
 
0.4%
전주덕진경찰서 1
 
0.4%
논산경찰서 1
 
0.4%
서산경찰서 1
 
0.4%
서천경찰서 1
 
0.4%
Other values (272) 272
96.5%
2024-03-23T06:17:56.684381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
315
18.4%
285
16.7%
277
16.2%
72
 
4.2%
45
 
2.6%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.6%
25
 
1.5%
Other values (144) 554
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1710
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
315
18.4%
285
16.7%
277
16.2%
72
 
4.2%
45
 
2.6%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.6%
25
 
1.5%
Other values (144) 554
32.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1710
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
315
18.4%
285
16.7%
277
16.2%
72
 
4.2%
45
 
2.6%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.6%
25
 
1.5%
Other values (144) 554
32.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1710
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
315
18.4%
285
16.7%
277
16.2%
72
 
4.2%
45
 
2.6%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.6%
25
 
1.5%
Other values (144) 554
32.4%

종합만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.632624
Minimum86.7
Maximum99.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:17:57.197610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.7
5-th percentile92.905
Q195
median95.9
Q396.6
95-th percentile97.9
Maximum99.2
Range12.5
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.6423877
Coefficient of variation (CV)0.017173927
Kurtosis4.3484082
Mean95.632624
Median Absolute Deviation (MAD)0.8
Skewness-1.4449961
Sum26968.4
Variance2.6974372
MonotonicityNot monotonic
2024-03-23T06:17:57.760110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.8 18
 
6.4%
96.2 12
 
4.3%
96.6 12
 
4.3%
96.1 12
 
4.3%
96.4 11
 
3.9%
95.4 10
 
3.5%
95.5 9
 
3.2%
96.5 9
 
3.2%
96.3 9
 
3.2%
95.2 9
 
3.2%
Other values (62) 171
60.6%
ValueCountFrequency (%)
86.7 1
0.4%
89.6 1
0.4%
90.1 2
0.7%
90.4 2
0.7%
91.1 1
0.4%
91.3 1
0.4%
91.6 2
0.7%
91.8 1
0.4%
91.9 1
0.4%
92.2 1
0.4%
ValueCountFrequency (%)
99.2 1
0.4%
98.9 1
0.4%
98.7 1
0.4%
98.6 1
0.4%
98.5 1
0.4%
98.4 1
0.4%
98.3 1
0.4%
98.2 2
0.7%
98.1 2
0.7%
98.0 1
0.4%

전반적만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.978014
Minimum84.7
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:17:58.506470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84.7
5-th percentile91.805
Q194.2
median95.25
Q396.2
95-th percentile97.495
Maximum100
Range15.3
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8962068
Coefficient of variation (CV)0.019964692
Kurtosis4.2621651
Mean94.978014
Median Absolute Deviation (MAD)0.95
Skewness-1.393136
Sum26783.8
Variance3.5956003
MonotonicityNot monotonic
2024-03-23T06:17:59.076280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.2 13
 
4.6%
95.6 13
 
4.6%
94.9 12
 
4.3%
96.2 12
 
4.3%
95.3 11
 
3.9%
96.1 10
 
3.5%
96.3 9
 
3.2%
96.6 9
 
3.2%
95.7 9
 
3.2%
95.9 8
 
2.8%
Other values (69) 176
62.4%
ValueCountFrequency (%)
84.7 1
0.4%
88.0 1
0.4%
88.5 1
0.4%
89.0 2
0.7%
89.1 1
0.4%
89.6 1
0.4%
90.1 1
0.4%
90.2 1
0.4%
90.5 1
0.4%
90.6 1
0.4%
ValueCountFrequency (%)
100.0 1
 
0.4%
99.3 1
 
0.4%
98.8 1
 
0.4%
98.2 1
 
0.4%
98.0 3
1.1%
97.9 2
0.7%
97.8 1
 
0.4%
97.7 2
0.7%
97.6 1
 
0.4%
97.5 2
0.7%

요소만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.920213
Minimum87.5
Maximum99.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:17:59.810773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87.5
5-th percentile93.305
Q195.3
median96.15
Q396.8
95-th percentile98.095
Maximum99.6
Range12.1
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.5559949
Coefficient of variation (CV)0.016221763
Kurtosis4.3529302
Mean95.920213
Median Absolute Deviation (MAD)0.7
Skewness-1.3914794
Sum27049.5
Variance2.4211202
MonotonicityNot monotonic
2024-03-23T06:18:00.362106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.8 15
 
5.3%
96.5 14
 
5.0%
96.1 13
 
4.6%
96.7 13
 
4.6%
96.3 12
 
4.3%
96.0 11
 
3.9%
97.0 10
 
3.5%
96.2 10
 
3.5%
96.4 10
 
3.5%
95.5 9
 
3.2%
Other values (58) 165
58.5%
ValueCountFrequency (%)
87.5 1
0.4%
90.3 1
0.4%
90.5 1
0.4%
90.8 1
0.4%
90.9 1
0.4%
91.0 1
0.4%
91.4 1
0.4%
92.0 1
0.4%
92.2 2
0.7%
92.3 2
0.7%
ValueCountFrequency (%)
99.6 1
 
0.4%
99.3 1
 
0.4%
99.2 1
 
0.4%
98.8 1
 
0.4%
98.6 2
 
0.7%
98.5 1
 
0.4%
98.4 1
 
0.4%
98.3 2
 
0.7%
98.1 5
1.8%
98.0 3
1.1%

업무처리절차 및 과정
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.852837
Minimum86.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:00.843870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.4
5-th percentile93.01
Q195.2
median96
Q396.8
95-th percentile98
Maximum100
Range13.6
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.5979777
Coefficient of variation (CV)0.016671157
Kurtosis5.2465004
Mean95.852837
Median Absolute Deviation (MAD)0.8
Skewness-1.3408103
Sum27030.5
Variance2.5535328
MonotonicityNot monotonic
2024-03-23T06:18:01.238677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.3 16
 
5.7%
96.4 13
 
4.6%
95.5 13
 
4.6%
95.9 13
 
4.6%
96.5 10
 
3.5%
96.0 10
 
3.5%
96.8 9
 
3.2%
95.7 9
 
3.2%
96.2 8
 
2.8%
95.2 8
 
2.8%
Other values (56) 173
61.3%
ValueCountFrequency (%)
86.4 1
 
0.4%
90.3 1
 
0.4%
90.9 1
 
0.4%
91.0 4
1.4%
91.3 1
 
0.4%
92.2 1
 
0.4%
92.4 1
 
0.4%
92.7 2
0.7%
93.0 3
1.1%
93.2 1
 
0.4%
ValueCountFrequency (%)
100.0 1
0.4%
99.6 1
0.4%
99.5 1
0.4%
99.2 1
0.4%
98.9 1
0.4%
98.8 1
0.4%
98.7 1
0.4%
98.5 1
0.4%
98.4 1
0.4%
98.3 1
0.4%

담당자응대태도
Real number (ℝ)

HIGH CORRELATION 

Distinct69
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.378369
Minimum88.9
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:01.893958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88.9
5-th percentile93.5
Q195.8
median96.7
Q397.4
95-th percentile98.695
Maximum100
Range11.1
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.6528397
Coefficient of variation (CV)0.017149489
Kurtosis3.0220836
Mean96.378369
Median Absolute Deviation (MAD)0.8
Skewness-1.3357654
Sum27178.7
Variance2.7318792
MonotonicityNot monotonic
2024-03-23T06:18:02.471975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.7 15
 
5.3%
96.9 14
 
5.0%
97.0 12
 
4.3%
97.4 12
 
4.3%
97.3 10
 
3.5%
97.5 10
 
3.5%
97.1 10
 
3.5%
96.3 9
 
3.2%
96.8 9
 
3.2%
96.2 8
 
2.8%
Other values (59) 173
61.3%
ValueCountFrequency (%)
88.9 1
0.4%
90.2 1
0.4%
90.7 2
0.7%
90.8 1
0.4%
91.3 1
0.4%
91.8 1
0.4%
92.0 1
0.4%
92.1 2
0.7%
92.3 1
0.4%
92.6 1
0.4%
ValueCountFrequency (%)
100.0 1
 
0.4%
99.5 1
 
0.4%
99.3 2
0.7%
99.2 1
 
0.4%
99.1 1
 
0.4%
99.0 1
 
0.4%
98.9 1
 
0.4%
98.8 3
1.1%
98.7 4
1.4%
98.6 2
0.7%

서비스품질
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.383333
Minimum87.7
Maximum99.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:03.067206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87.7
5-th percentile94.1
Q195.9
median96.6
Q397.2
95-th percentile98.495
Maximum99.4
Range11.7
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.4709424
Coefficient of variation (CV)0.015261377
Kurtosis6.7916277
Mean96.383333
Median Absolute Deviation (MAD)0.65
Skewness-1.7498746
Sum27180.1
Variance2.1636714
MonotonicityNot monotonic
2024-03-23T06:18:03.638661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.8 19
 
6.7%
97.0 14
 
5.0%
96.3 14
 
5.0%
96.1 13
 
4.6%
96.7 12
 
4.3%
97.1 12
 
4.3%
97.3 12
 
4.3%
96.6 11
 
3.9%
96.2 11
 
3.9%
96.5 11
 
3.9%
Other values (51) 153
54.3%
ValueCountFrequency (%)
87.7 1
0.4%
89.0 1
0.4%
90.9 1
0.4%
91.5 1
0.4%
91.8 1
0.4%
92.6 2
0.7%
92.8 1
0.4%
93.0 1
0.4%
93.1 1
0.4%
93.3 1
0.4%
ValueCountFrequency (%)
99.4 1
 
0.4%
99.1 1
 
0.4%
99.0 2
0.7%
98.8 4
1.4%
98.7 1
 
0.4%
98.6 4
1.4%
98.5 2
0.7%
98.4 1
 
0.4%
98.3 2
0.7%
98.2 3
1.1%

시설 및 이용환경
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.945035
Minimum86.7
Maximum99.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:04.320113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.7
5-th percentile91.615
Q194.1
median95.2
Q396
95-th percentile97.395
Maximum99.3
Range12.6
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.8020333
Coefficient of variation (CV)0.018979753
Kurtosis3.2358716
Mean94.945035
Median Absolute Deviation (MAD)1
Skewness-1.2254178
Sum26774.5
Variance3.247324
MonotonicityNot monotonic
2024-03-23T06:18:04.992209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.7 15
 
5.3%
95.6 14
 
5.0%
94.9 11
 
3.9%
95.9 11
 
3.9%
96.2 10
 
3.5%
94.8 10
 
3.5%
95.0 9
 
3.2%
96.4 8
 
2.8%
95.5 7
 
2.5%
94.6 7
 
2.5%
Other values (65) 180
63.8%
ValueCountFrequency (%)
86.7 1
0.4%
87.1 1
0.4%
87.8 1
0.4%
89.6 1
0.4%
89.7 1
0.4%
89.8 1
0.4%
90.7 1
0.4%
90.8 2
0.7%
91.0 1
0.4%
91.3 1
0.4%
ValueCountFrequency (%)
99.3 1
0.4%
99.0 1
0.4%
98.8 1
0.4%
98.1 1
0.4%
98.0 1
0.4%
97.9 1
0.4%
97.8 1
0.4%
97.7 1
0.4%
97.6 1
0.4%
97.5 1
0.4%

신속성
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.067021
Minimum86.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:05.678762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.3
5-th percentile93.805
Q195.3
median96.2
Q396.9
95-th percentile98.095
Maximum100
Range13.7
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.4644583
Coefficient of variation (CV)0.015244131
Kurtosis7.4839822
Mean96.067021
Median Absolute Deviation (MAD)0.8
Skewness-1.4742065
Sum27090.9
Variance2.1446381
MonotonicityNot monotonic
2024-03-23T06:18:06.152229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.4 14
 
5.0%
96.7 13
 
4.6%
95.3 12
 
4.3%
96.3 12
 
4.3%
95.7 11
 
3.9%
96.5 11
 
3.9%
95.9 11
 
3.9%
96.9 9
 
3.2%
95.1 9
 
3.2%
95.4 9
 
3.2%
Other values (54) 171
60.6%
ValueCountFrequency (%)
86.3 1
0.4%
90.8 1
0.4%
91.5 1
0.4%
91.7 1
0.4%
91.8 1
0.4%
91.9 1
0.4%
92.4 1
0.4%
92.7 1
0.4%
93.2 1
0.4%
93.3 2
0.7%
ValueCountFrequency (%)
100.0 1
 
0.4%
99.3 1
 
0.4%
99.2 1
 
0.4%
99.0 2
0.7%
98.9 1
 
0.4%
98.6 2
0.7%
98.5 2
0.7%
98.3 1
 
0.4%
98.2 3
1.1%
98.1 1
 
0.4%

지원성
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.639362
Minimum86.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:06.621092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.4
5-th percentile92.405
Q194.9
median95.9
Q396.6
95-th percentile98.1
Maximum100
Range13.6
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation1.7990241
Coefficient of variation (CV)0.018810499
Kurtosis3.8931313
Mean95.639362
Median Absolute Deviation (MAD)0.85
Skewness-1.299767
Sum26970.3
Variance3.2364878
MonotonicityNot monotonic
2024-03-23T06:18:07.142330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.4 13
 
4.6%
95.9 12
 
4.3%
96.3 12
 
4.3%
96.1 11
 
3.9%
96.6 11
 
3.9%
96.7 10
 
3.5%
95.8 10
 
3.5%
94.9 9
 
3.2%
95.7 9
 
3.2%
96.5 9
 
3.2%
Other values (60) 176
62.4%
ValueCountFrequency (%)
86.4 1
0.4%
89.3 1
0.4%
89.5 1
0.4%
89.8 1
0.4%
89.9 1
0.4%
90.2 1
0.4%
90.3 1
0.4%
90.6 1
0.4%
90.8 1
0.4%
91.0 1
0.4%
ValueCountFrequency (%)
100.0 3
1.1%
99.3 1
 
0.4%
98.7 3
1.1%
98.4 2
 
0.7%
98.2 5
1.8%
98.1 4
1.4%
97.9 2
 
0.7%
97.8 2
 
0.7%
97.7 1
 
0.4%
97.6 2
 
0.7%

성실성
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.439007
Minimum86.9
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:07.579615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.9
5-th percentile91.61
Q194.6
median95.9
Q396.775
95-th percentile98.3
Maximum100
Range13.1
Interquartile range (IQR)2.175

Descriptive statistics

Standard deviation2.1932855
Coefficient of variation (CV)0.022981018
Kurtosis2.686869
Mean95.439007
Median Absolute Deviation (MAD)1
Skewness-1.3027579
Sum26913.8
Variance4.8105015
MonotonicityNot monotonic
2024-03-23T06:18:08.313341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97.0 13
 
4.6%
95.9 13
 
4.6%
96.3 11
 
3.9%
96.7 10
 
3.5%
95.7 10
 
3.5%
95.8 9
 
3.2%
96.9 9
 
3.2%
95.0 9
 
3.2%
96.6 9
 
3.2%
95.4 8
 
2.8%
Other values (71) 181
64.2%
ValueCountFrequency (%)
86.9 1
0.4%
87.1 1
0.4%
87.5 1
0.4%
88.0 1
0.4%
88.1 1
0.4%
88.4 1
0.4%
88.8 1
0.4%
88.9 1
0.4%
89.5 1
0.4%
90.0 1
0.4%
ValueCountFrequency (%)
100.0 3
1.1%
99.0 3
1.1%
98.8 2
0.7%
98.7 2
0.7%
98.5 2
0.7%
98.4 2
0.7%
98.3 2
0.7%
98.2 2
0.7%
98.1 3
1.1%
97.9 2
0.7%

청렴성
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.318794
Minimum90.7
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:09.281960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90.7
5-th percentile95.4
Q196.825
median97.5
Q398
95-th percentile98.9
Maximum100
Range9.3
Interquartile range (IQR)1.175

Descriptive statistics

Standard deviation1.2015861
Coefficient of variation (CV)0.012346907
Kurtosis6.0584599
Mean97.318794
Median Absolute Deviation (MAD)0.6
Skewness-1.7186648
Sum27443.9
Variance1.4438092
MonotonicityNot monotonic
2024-03-23T06:18:09.874647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97.6 23
 
8.2%
97.4 18
 
6.4%
97.7 15
 
5.3%
97.5 13
 
4.6%
98.3 13
 
4.6%
98.0 12
 
4.3%
97.8 11
 
3.9%
97.9 10
 
3.5%
97.0 10
 
3.5%
98.1 10
 
3.5%
Other values (44) 147
52.1%
ValueCountFrequency (%)
90.7 1
0.4%
91.3 1
0.4%
92.9 2
0.7%
93.5 1
0.4%
93.8 1
0.4%
94.1 1
0.4%
94.4 1
0.4%
94.6 1
0.4%
94.7 1
0.4%
95.1 2
0.7%
ValueCountFrequency (%)
100.0 1
 
0.4%
99.8 1
 
0.4%
99.4 2
 
0.7%
99.3 1
 
0.4%
99.2 2
 
0.7%
99.1 2
 
0.7%
99.0 3
1.1%
98.9 5
1.8%
98.8 4
1.4%
98.7 2
 
0.7%

전문성
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.757447
Minimum86.7
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:10.452545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.7
5-th percentile92.91
Q195.125
median96.05
Q396.7
95-th percentile98.195
Maximum99
Range12.3
Interquartile range (IQR)1.575

Descriptive statistics

Standard deviation1.6750943
Coefficient of variation (CV)0.017493097
Kurtosis5.5615303
Mean95.757447
Median Absolute Deviation (MAD)0.75
Skewness-1.5963879
Sum27003.6
Variance2.8059408
MonotonicityNot monotonic
2024-03-23T06:18:10.911232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.1 15
 
5.3%
96.2 15
 
5.3%
95.5 14
 
5.0%
96.5 13
 
4.6%
96.6 13
 
4.6%
96.8 11
 
3.9%
95.9 9
 
3.2%
95.8 9
 
3.2%
95.3 9
 
3.2%
97.2 8
 
2.8%
Other values (57) 166
58.9%
ValueCountFrequency (%)
86.7 1
0.4%
87.3 1
0.4%
89.7 1
0.4%
90.3 1
0.4%
90.4 1
0.4%
91.1 1
0.4%
91.3 1
0.4%
91.8 1
0.4%
92.1 1
0.4%
92.3 2
0.7%
ValueCountFrequency (%)
99.0 1
 
0.4%
98.8 2
 
0.7%
98.6 3
1.1%
98.5 5
1.8%
98.2 4
1.4%
98.1 2
 
0.7%
98.0 1
 
0.4%
97.9 2
 
0.7%
97.8 3
1.1%
97.7 2
 
0.7%

공정성
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.008156
Minimum88.6
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:11.444436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88.6
5-th percentile94.905
Q196.5
median97.2
Q397.7
95-th percentile98.7
Maximum100
Range11.4
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.3070453
Coefficient of variation (CV)0.013473561
Kurtosis8.107089
Mean97.008156
Median Absolute Deviation (MAD)0.6
Skewness-1.8088144
Sum27356.3
Variance1.7083674
MonotonicityNot monotonic
2024-03-23T06:18:12.031743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97.2 15
 
5.3%
96.9 15
 
5.3%
97.1 14
 
5.0%
97.8 14
 
5.0%
97.6 13
 
4.6%
97.7 12
 
4.3%
96.6 11
 
3.9%
97.3 11
 
3.9%
97.5 11
 
3.9%
97.4 10
 
3.5%
Other values (47) 156
55.3%
ValueCountFrequency (%)
88.6 1
 
0.4%
90.7 1
 
0.4%
92.2 1
 
0.4%
92.8 1
 
0.4%
93.3 2
0.7%
93.9 1
 
0.4%
94.0 2
0.7%
94.3 1
 
0.4%
94.6 3
1.1%
94.8 1
 
0.4%
ValueCountFrequency (%)
100.0 2
 
0.7%
99.5 1
 
0.4%
99.4 1
 
0.4%
99.2 3
1.1%
99.1 2
 
0.7%
99.0 2
 
0.7%
98.9 1
 
0.4%
98.8 2
 
0.7%
98.7 2
 
0.7%
98.6 5
1.8%

편리성
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.945035
Minimum86.7
Maximum99.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:18:12.564052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.7
5-th percentile91.615
Q194.1
median95.2
Q396
95-th percentile97.395
Maximum99.3
Range12.6
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.8020333
Coefficient of variation (CV)0.018979753
Kurtosis3.2358716
Mean94.945035
Median Absolute Deviation (MAD)1
Skewness-1.2254178
Sum26774.5
Variance3.247324
MonotonicityNot monotonic
2024-03-23T06:18:13.246085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.7 15
 
5.3%
95.6 14
 
5.0%
94.9 11
 
3.9%
95.9 11
 
3.9%
96.2 10
 
3.5%
94.8 10
 
3.5%
95.0 9
 
3.2%
96.4 8
 
2.8%
95.5 7
 
2.5%
94.6 7
 
2.5%
Other values (65) 180
63.8%
ValueCountFrequency (%)
86.7 1
0.4%
87.1 1
0.4%
87.8 1
0.4%
89.6 1
0.4%
89.7 1
0.4%
89.8 1
0.4%
90.7 1
0.4%
90.8 2
0.7%
91.0 1
0.4%
91.3 1
0.4%
ValueCountFrequency (%)
99.3 1
0.4%
99.0 1
0.4%
98.8 1
0.4%
98.1 1
0.4%
98.0 1
0.4%
97.9 1
0.4%
97.8 1
0.4%
97.7 1
0.4%
97.6 1
0.4%
97.5 1
0.4%

Interactions

2024-03-23T06:17:48.654202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:43.525894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:49.020576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:53.869134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:59.620854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:04.516739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:08.704837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:14.385352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:19.418016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:23.828223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:29.825705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:34.580218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:39.475051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:43.120906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:48.916008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:43.963156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:49.399281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:54.281482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:00.079705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:04.811065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:09.067608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:14.863239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:19.727592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:24.347043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:30.290027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:34.850953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:39.791577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:43.497358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:49.322594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:44.304121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:49.821351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:54.640400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:00.396639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:05.110448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:09.444597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:15.403900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:20.020457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:25.187960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:30.636134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:35.270672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:40.059502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:43.896485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:49.626342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:44.812333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:50.197700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:55.053560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:00.715711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:05.368424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:10.051239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:15.789517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:20.364221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:25.500929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:31.017764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:35.656463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:40.328233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:44.293922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:49.929942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:45.304366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:50.519034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:55.449241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:01.070605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:05.651614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:10.762829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:16.198486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:20.676768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:25.805749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:31.373587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:35.939177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:40.590106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:44.721135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:50.187165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:45.619124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:50.797801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:55.786085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:01.496502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:05.903739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:11.204830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:16.550223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:20.966691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:26.088054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:31.630147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:36.238687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:40.903043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:45.020910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:50.519343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:45.990202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:51.055882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:56.232702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:01.820565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:06.243687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:11.626059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:16.820721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:21.205316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:26.387211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:31.880035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:36.589696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:41.142934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:45.704767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:50.797359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:46.365883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:51.538696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:56.622691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:02.130611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:06.563217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:11.891333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:17.202336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:21.484649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:26.719137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:32.256674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:37.004915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:41.354811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:46.106268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:51.065065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:46.873265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:51.785895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:57.217356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:02.539383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:06.814053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:12.188590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:17.540039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:21.867595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:27.170246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:32.571055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:37.361676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:41.593345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:46.560594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:51.377692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:47.221663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:52.073682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:57.819960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:02.831427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:07.209093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:12.873020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:17.884665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:22.159137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:27.628109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:32.832510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:37.867214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:41.869922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:47.007899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:51.827794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:47.527331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:52.441137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:58.235900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:03.158099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:07.533293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:13.211926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:18.146547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:22.438137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:28.006209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:33.085412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:38.245060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:42.101574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:47.287720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:52.088796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:47.879128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:52.860253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:58.518816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:03.364922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:07.772578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:13.571973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:18.403214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:22.709417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:28.431770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:33.658431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:38.600391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:42.367095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:47.707730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:52.339996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:48.264586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:53.192039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:58.888269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:03.789112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:08.026437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:13.871493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:18.704682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:23.009130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:28.862076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:33.997130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:38.841454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:42.608759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:48.041745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:52.591846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:48.673035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:53.511145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:16:59.257513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:04.088694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:08.329273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:14.122830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:18.984058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:23.362010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:29.326535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:34.269822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:39.185877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:42.852623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:17:48.381323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:18:13.621286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.9800.9920.9760.9130.9000.9430.9020.9660.8610.9550.9410.9580.943
전반적만족도0.9801.0000.9830.9660.9150.8940.9220.8750.9740.8540.9290.9410.9440.922
요소만족도0.9920.9831.0000.9830.9280.8910.9400.9060.9750.8790.9430.9320.9550.940
업무처리절차 및 과정0.9760.9660.9831.0000.9120.8880.9150.9360.9820.8570.9570.9530.9640.915
담당자응대태도0.9130.9150.9280.9121.0000.9580.7980.8800.9180.9710.8620.8490.8730.798
서비스품질0.9000.8940.8910.8880.9581.0000.7580.8840.8800.9260.8960.9350.9530.758
시설 및 이용환경0.9430.9220.9400.9150.7980.7581.0000.8220.9040.7770.8680.8560.8801.000
신속성0.9020.8750.9060.9360.8800.8840.8221.0000.8900.8260.8360.8310.8930.822
지원성0.9660.9740.9750.9820.9180.8800.9040.8901.0000.8830.9220.9390.9480.904
성실성0.8610.8540.8790.8570.9710.9260.7770.8260.8831.0000.8000.8110.8220.777
청렴성0.9550.9290.9430.9570.8620.8960.8680.8360.9220.8001.0000.9760.9750.868
전문성0.9410.9410.9320.9530.8490.9350.8560.8310.9390.8110.9761.0000.9730.856
공정성0.9580.9440.9550.9640.8730.9530.8800.8930.9480.8220.9750.9731.0000.880
편리성0.9430.9220.9400.9150.7980.7581.0000.8220.9040.7770.8680.8560.8801.000
2024-03-23T06:18:14.170771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.9880.9960.9680.9620.9580.8640.9260.9590.9520.9110.9470.9190.864
전반적만족도0.9881.0000.9730.9560.9480.9400.8340.9150.9480.9440.8860.9330.8950.834
요소만족도0.9960.9731.0000.9650.9610.9590.8750.9220.9550.9480.9170.9460.9220.875
업무처리절차 및 과정0.9680.9560.9651.0000.9350.9400.7790.9690.9750.9270.8850.9370.8910.779
담당자응대태도0.9620.9480.9610.9351.0000.9460.7650.8820.9370.9840.9540.9330.9100.765
서비스품질0.9580.9400.9590.9400.9461.0000.7570.9020.9300.9180.9320.9770.9660.757
시설 및 이용환경0.8640.8340.8750.7790.7650.7571.0000.7420.7730.7620.7230.7460.7381.000
신속성0.9260.9150.9220.9690.8820.9020.7421.0000.8960.8680.8500.8980.8610.742
지원성0.9590.9480.9550.9750.9370.9300.7730.8961.0000.9350.8750.9240.8780.773
성실성0.9520.9440.9480.9270.9840.9180.7620.8680.9351.0000.8920.9210.8640.762
청렴성0.9110.8860.9170.8850.9540.9320.7230.8500.8750.8921.0000.8920.9310.723
전문성0.9470.9330.9460.9370.9330.9770.7460.8980.9240.9210.8921.0000.8960.746
공정성0.9190.8950.9220.8910.9100.9660.7380.8610.8780.8640.9310.8961.0000.738
편리성0.8640.8340.8750.7790.7650.7571.0000.7420.7730.7620.7230.7460.7381.000

Missing values

2024-03-23T06:17:53.047334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:17:53.987217image/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

응답자특성종합만족도전반적만족도요소만족도업무처리절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
0기타민원94.293.294.794.595.794.494.094.594.695.296.294.394.694.0
1수사민원86.784.787.586.488.987.787.186.386.487.190.786.788.687.1
2유실물96.295.796.496.397.096.895.696.596.196.397.696.297.495.6
3총포화약96.596.196.796.797.997.095.096.597.097.498.596.597.695.0
4교통민원95.094.295.395.495.796.194.095.895.094.397.195.496.894.0
5서울특별시경찰청95.394.695.695.596.196.394.196.095.094.797.595.797.094.1
6부산광역시경찰청96.495.996.696.797.197.195.496.996.696.597.896.697.695.4
7대구광역시경찰청95.895.296.196.296.596.695.096.595.995.797.496.097.295.0
8인천광역시경찰청96.595.996.796.797.497.295.696.796.696.897.996.897.695.6
9광주광역시경찰청95.494.795.795.996.296.294.496.195.795.297.195.596.894.4
응답자특성종합만족도전반적만족도요소만족도업무처리절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
272경남고성경찰서94.193.194.694.794.694.993.995.194.392.796.694.295.793.9
273하동경찰서95.895.695.996.396.396.494.696.396.395.896.796.096.994.6
274남해경찰서96.195.396.495.997.096.896.196.095.795.798.395.997.796.1
275함양경찰서98.698.898.598.498.898.797.998.598.298.898.898.299.197.9
276산청경찰서96.195.396.496.397.595.796.396.296.496.898.295.396.096.3
277함안경찰서96.696.296.896.697.596.796.296.796.696.798.495.597.996.2
278의령경찰서97.596.697.997.698.398.297.197.797.697.898.897.998.697.1
279제주동부경찰서93.491.994.093.894.394.693.294.693.092.496.393.495.893.2
280제주서부경찰서95.795.395.895.996.796.394.396.095.895.597.895.197.594.3
281서귀포경찰서94.893.995.295.095.795.494.595.794.394.397.094.396.494.5