Overview

Dataset statistics

Number of variables15
Number of observations277
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.4 KiB
Average record size in memory134.5 B

Variable types

Text1
Numeric14

Dataset

Description경찰청 교통분야 치안고객만족도(관서별) 분야(응답자 특성, 종합만족도, 전반적만족도, 요소만족도, 업무처리절차 및 과정, 담당자응대태도, 서비스품질, 시설및이용환경, 신속성 지원성, 성실성, 청렴성, 전문성, 공정성, 편리성)
Author경찰청
URLhttps://www.data.go.kr/data/15064404/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
업무처리 절차 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 04:20:11.464116
Analysis finished2024-03-23 04:21:25.383797
Duration1 minute and 13.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

응답자특성
Text

UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-03-23T04:21:25.910999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.1046931
Min length5

Characters and Unicode

Total characters1691
Distinct characters148
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

Unique277 ?
Unique (%)100.0%

Sample

1st row서울특별시경찰청
2nd row부산광역시경찰청
3rd row대구광역시경찰청
4th row인천광역시경찰청
5th row광주광역시경찰청
ValueCountFrequency (%)
서울특별시경찰청 1
 
0.4%
천안서북경찰서 1
 
0.4%
태안경찰서 1
 
0.4%
청양경찰서 1
 
0.4%
금산경찰서 1
 
0.4%
서천경찰서 1
 
0.4%
부여경찰서 1
 
0.4%
예산경찰서 1
 
0.4%
당진경찰서 1
 
0.4%
양주경찰서 1
 
0.4%
Other values (267) 267
96.4%
2024-03-23T04:21:27.212564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
315
18.6%
285
16.9%
277
16.4%
72
 
4.3%
45
 
2.7%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.7%
25
 
1.5%
Other values (138) 535
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1691
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
315
18.6%
285
16.9%
277
16.4%
72
 
4.3%
45
 
2.7%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.7%
25
 
1.5%
Other values (138) 535
31.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1691
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
315
18.6%
285
16.9%
277
16.4%
72
 
4.3%
45
 
2.7%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.7%
25
 
1.5%
Other values (138) 535
31.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1691
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
315
18.6%
285
16.9%
277
16.4%
72
 
4.3%
45
 
2.7%
41
 
2.4%
36
 
2.1%
32
 
1.9%
28
 
1.7%
25
 
1.5%
Other values (138) 535
31.6%

종합만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.745848
Minimum67
Maximum99.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:27.898788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile77.2
Q183.6
median86.8
Q390.4
95-th percentile95.96
Maximum99.8
Range32.8
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation5.5119132
Coefficient of variation (CV)0.063540946
Kurtosis0.089361752
Mean86.745848
Median Absolute Deviation (MAD)3.4
Skewness-0.23041136
Sum24028.6
Variance30.381187
MonotonicityNot monotonic
2024-03-23T04:21:28.425561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.8 6
 
2.2%
91.0 5
 
1.8%
90.4 5
 
1.8%
86.0 4
 
1.4%
88.5 4
 
1.4%
86.8 4
 
1.4%
85.4 4
 
1.4%
87.7 4
 
1.4%
85.5 4
 
1.4%
84.4 4
 
1.4%
Other values (141) 233
84.1%
ValueCountFrequency (%)
67.0 1
 
0.4%
72.3 1
 
0.4%
73.5 1
 
0.4%
74.2 1
 
0.4%
75.0 1
 
0.4%
75.2 1
 
0.4%
75.4 1
 
0.4%
76.0 1
 
0.4%
76.9 1
 
0.4%
77.1 3
1.1%
ValueCountFrequency (%)
99.8 1
0.4%
99.1 1
0.4%
97.8 2
0.7%
97.6 1
0.4%
97.4 1
0.4%
97.2 1
0.4%
97.0 1
0.4%
96.8 2
0.7%
96.5 2
0.7%
96.3 1
0.4%

전반적만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct153
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.742238
Minimum58
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:29.220727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile73.08
Q180.7
median84.7
Q388.9
95-th percentile97.5
Maximum100
Range42
Interquartile range (IQR)8.2

Descriptive statistics

Standard deviation7.1987207
Coefficient of variation (CV)0.084948437
Kurtosis0.4388972
Mean84.742238
Median Absolute Deviation (MAD)4
Skewness-0.1262953
Sum23473.6
Variance51.821579
MonotonicityNot monotonic
2024-03-23T04:21:29.830966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 9
 
3.2%
81.8 6
 
2.2%
85.7 5
 
1.8%
75.0 5
 
1.8%
80.7 5
 
1.8%
83.0 4
 
1.4%
85.0 4
 
1.4%
95.0 4
 
1.4%
87.9 4
 
1.4%
81.7 4
 
1.4%
Other values (143) 227
81.9%
ValueCountFrequency (%)
58.0 1
 
0.4%
63.7 1
 
0.4%
66.0 1
 
0.4%
67.0 1
 
0.4%
69.5 1
 
0.4%
69.8 1
 
0.4%
71.5 1
 
0.4%
71.6 1
 
0.4%
72.0 1
 
0.4%
72.4 3
1.1%
ValueCountFrequency (%)
100.0 9
3.2%
98.8 3
 
1.1%
98.0 1
 
0.4%
97.5 2
 
0.7%
97.1 2
 
0.7%
97.0 1
 
0.4%
96.8 1
 
0.4%
96.7 1
 
0.4%
96.6 1
 
0.4%
96.0 1
 
0.4%

요소만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.812996
Minimum68.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:30.361263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68.4
5-th percentile78.96
Q184.6
median87.6
Q391.1
95-th percentile98.34
Maximum100
Range31.6
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.7447497
Coefficient of variation (CV)0.065420268
Kurtosis0.26475689
Mean87.812996
Median Absolute Deviation (MAD)3.3
Skewness-0.038696407
Sum24324.2
Variance33.002149
MonotonicityNot monotonic
2024-03-23T04:21:30.942635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
87.7 6
 
2.2%
87.0 6
 
2.2%
100.0 6
 
2.2%
86.4 5
 
1.8%
89.0 5
 
1.8%
85.3 5
 
1.8%
79.1 4
 
1.4%
85.7 4
 
1.4%
89.4 4
 
1.4%
85.9 4
 
1.4%
Other values (134) 228
82.3%
ValueCountFrequency (%)
68.4 1
0.4%
69.7 1
0.4%
74.6 1
0.4%
75.2 2
0.7%
76.7 2
0.7%
77.2 1
0.4%
77.7 1
0.4%
77.8 1
0.4%
78.4 1
0.4%
78.7 1
0.4%
ValueCountFrequency (%)
100.0 6
2.2%
99.7 1
 
0.4%
99.4 1
 
0.4%
99.3 2
 
0.7%
99.2 2
 
0.7%
98.6 1
 
0.4%
98.5 1
 
0.4%
98.3 2
 
0.7%
98.1 3
1.1%
97.9 1
 
0.4%

업무처리 절차 및 과정
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.701444
Minimum60
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:31.519970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile75.08
Q181.9
median85.3
Q389.6
95-th percentile98.92
Maximum100
Range40
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation6.9217729
Coefficient of variation (CV)0.080766117
Kurtosis0.73798419
Mean85.701444
Median Absolute Deviation (MAD)4.1
Skewness-0.15197572
Sum23739.3
Variance47.91094
MonotonicityNot monotonic
2024-03-23T04:21:32.205769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 10
 
3.6%
84.8 5
 
1.8%
88.3 5
 
1.8%
86.5 5
 
1.8%
90.0 5
 
1.8%
83.1 4
 
1.4%
84.0 4
 
1.4%
84.6 4
 
1.4%
84.2 4
 
1.4%
83.7 4
 
1.4%
Other values (148) 227
81.9%
ValueCountFrequency (%)
60.0 1
0.4%
62.0 1
0.4%
64.5 1
0.4%
70.6 1
0.4%
71.0 1
0.4%
71.8 1
0.4%
72.5 1
0.4%
72.8 1
0.4%
73.3 1
0.4%
73.9 2
0.7%
ValueCountFrequency (%)
100.0 10
3.6%
99.4 4
 
1.4%
98.8 1
 
0.4%
98.3 1
 
0.4%
98.1 1
 
0.4%
97.7 1
 
0.4%
97.6 1
 
0.4%
97.0 1
 
0.4%
96.9 2
 
0.7%
96.8 1
 
0.4%

담당자응대태도
Real number (ℝ)

HIGH CORRELATION 

Distinct140
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.231047
Minimum70
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:32.852034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile80.8
Q186.1
median89.1
Q392.3
95-th percentile99.84
Maximum100
Range30
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation5.5266066
Coefficient of variation (CV)0.061935916
Kurtosis0.34990553
Mean89.231047
Median Absolute Deviation (MAD)3.2
Skewness-0.1339947
Sum24717
Variance30.54338
MonotonicityNot monotonic
2024-03-23T04:21:33.295382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 14
 
5.1%
88.3 6
 
2.2%
89.1 5
 
1.8%
88.4 5
 
1.8%
88.2 5
 
1.8%
88.8 4
 
1.4%
84.6 4
 
1.4%
92.1 4
 
1.4%
90.0 4
 
1.4%
89.4 4
 
1.4%
Other values (130) 222
80.1%
ValueCountFrequency (%)
70.0 1
0.4%
72.0 1
0.4%
74.5 1
0.4%
75.3 1
0.4%
76.0 1
0.4%
77.7 1
0.4%
78.2 1
0.4%
78.6 1
0.4%
78.8 1
0.4%
79.7 1
0.4%
ValueCountFrequency (%)
100.0 14
5.1%
99.8 1
 
0.4%
99.4 2
 
0.7%
99.0 2
 
0.7%
98.7 1
 
0.4%
98.6 1
 
0.4%
98.3 3
 
1.1%
97.6 1
 
0.4%
97.5 3
 
1.1%
96.9 2
 
0.7%

서비스품질
Real number (ℝ)

HIGH CORRELATION 

Distinct148
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.350181
Minimum66
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:34.054701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile78.84
Q185.2
median88.2
Q391.7
95-th percentile99.42
Maximum100
Range34
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.8320493
Coefficient of variation (CV)0.06601061
Kurtosis0.70835144
Mean88.350181
Median Absolute Deviation (MAD)3.2
Skewness-0.19214053
Sum24473
Variance34.012799
MonotonicityNot monotonic
2024-03-23T04:21:34.538909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 13
 
4.7%
85.8 6
 
2.2%
86.8 5
 
1.8%
86.3 5
 
1.8%
87.4 5
 
1.8%
89.8 5
 
1.8%
85.6 4
 
1.4%
87.3 4
 
1.4%
89.9 4
 
1.4%
93.8 4
 
1.4%
Other values (138) 222
80.1%
ValueCountFrequency (%)
66.0 1
0.4%
67.3 1
0.4%
74.8 1
0.4%
75.9 1
0.4%
76.3 1
0.4%
77.0 1
0.4%
77.8 1
0.4%
77.9 1
0.4%
78.0 1
0.4%
78.1 1
0.4%
ValueCountFrequency (%)
100.0 13
4.7%
99.5 1
 
0.4%
99.4 2
 
0.7%
98.9 1
 
0.4%
98.8 1
 
0.4%
98.6 1
 
0.4%
98.3 1
 
0.4%
98.1 2
 
0.7%
98.0 1
 
0.4%
97.9 1
 
0.4%

시설 및 이용환경
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.042238
Minimum68
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:34.976712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68
5-th percentile78.68
Q184.8
median87.9
Q391.3
95-th percentile97.62
Maximum100
Range32
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.5862006
Coefficient of variation (CV)0.063449098
Kurtosis0.35083782
Mean88.042238
Median Absolute Deviation (MAD)3.2
Skewness-0.11233425
Sum24387.7
Variance31.205637
MonotonicityNot monotonic
2024-03-23T04:21:35.446855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 10
 
3.6%
87.5 7
 
2.5%
87.9 6
 
2.2%
93.3 5
 
1.8%
84.7 5
 
1.8%
85.7 5
 
1.8%
85.6 5
 
1.8%
89.3 4
 
1.4%
90.0 4
 
1.4%
90.3 4
 
1.4%
Other values (134) 222
80.1%
ValueCountFrequency (%)
68.0 1
 
0.4%
70.3 1
 
0.4%
74.4 1
 
0.4%
77.3 1
 
0.4%
77.4 1
 
0.4%
77.5 2
0.7%
77.9 2
0.7%
78.1 1
 
0.4%
78.5 1
 
0.4%
78.6 3
1.1%
ValueCountFrequency (%)
100.0 10
3.6%
99.6 1
 
0.4%
98.9 1
 
0.4%
97.9 1
 
0.4%
97.7 1
 
0.4%
97.6 1
 
0.4%
97.5 1
 
0.4%
97.2 1
 
0.4%
97.1 1
 
0.4%
97.0 1
 
0.4%

신속성
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.236823
Minimum55
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:35.912734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55
5-th percentile73.72
Q181.1
median85
Q389.3
95-th percentile98.8
Maximum100
Range45
Interquartile range (IQR)8.2

Descriptive statistics

Standard deviation7.2900877
Coefficient of variation (CV)0.085527445
Kurtosis1.0128832
Mean85.236823
Median Absolute Deviation (MAD)4.2
Skewness-0.22868468
Sum23610.6
Variance53.145378
MonotonicityNot monotonic
2024-03-23T04:21:36.336512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 12
 
4.3%
85.0 6
 
2.2%
89.2 6
 
2.2%
80.0 5
 
1.8%
82.7 4
 
1.4%
87.4 4
 
1.4%
84.5 4
 
1.4%
85.1 4
 
1.4%
98.8 4
 
1.4%
81.4 4
 
1.4%
Other values (144) 224
80.9%
ValueCountFrequency (%)
55.0 1
0.4%
62.0 1
0.4%
64.0 1
0.4%
66.0 1
0.4%
69.4 1
0.4%
69.8 1
0.4%
70.1 1
0.4%
71.6 1
0.4%
72.3 1
0.4%
72.4 1
0.4%
ValueCountFrequency (%)
100.0 12
4.3%
98.9 1
 
0.4%
98.8 4
 
1.4%
98.7 1
 
0.4%
98.2 1
 
0.4%
97.5 1
 
0.4%
97.4 1
 
0.4%
97.1 1
 
0.4%
97.0 1
 
0.4%
96.7 1
 
0.4%

지원성
Real number (ℝ)

HIGH CORRELATION 

Distinct152
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.164621
Minimum62
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:36.836323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile75.56
Q182.6
median85.9
Q390
95-th percentile98.4
Maximum100
Range38
Interquartile range (IQR)7.4

Descriptive statistics

Standard deviation6.7417242
Coefficient of variation (CV)0.078242371
Kurtosis0.54959876
Mean86.164621
Median Absolute Deviation (MAD)3.8
Skewness-0.14157568
Sum23867.6
Variance45.450845
MonotonicityNot monotonic
2024-03-23T04:21:37.446070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 14
 
5.1%
85.1 7
 
2.5%
82.6 6
 
2.2%
90.0 5
 
1.8%
83.3 5
 
1.8%
83.8 5
 
1.8%
78.8 5
 
1.8%
84.0 4
 
1.4%
87.5 4
 
1.4%
84.2 4
 
1.4%
Other values (142) 218
78.7%
ValueCountFrequency (%)
62.0 1
0.4%
64.9 1
0.4%
65.0 1
0.4%
71.1 1
0.4%
72.3 1
0.4%
72.6 1
0.4%
73.8 1
0.4%
73.9 1
0.4%
74.0 1
0.4%
74.2 1
0.4%
ValueCountFrequency (%)
100.0 14
5.1%
98.0 1
 
0.4%
97.5 2
 
0.7%
97.2 1
 
0.4%
97.1 2
 
0.7%
96.8 1
 
0.4%
96.7 2
 
0.7%
96.6 1
 
0.4%
96.4 1
 
0.4%
96.3 2
 
0.7%

성실성
Real number (ℝ)

HIGH CORRELATION 

Distinct150
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.719495
Minimum66
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:38.073977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile77.6
Q183.9
median87.5
Q391.2
95-th percentile100
Maximum100
Range34
Interquartile range (IQR)7.3

Descriptive statistics

Standard deviation6.3693317
Coefficient of variation (CV)0.072610219
Kurtosis0.37026073
Mean87.719495
Median Absolute Deviation (MAD)3.7
Skewness-0.12375421
Sum24298.3
Variance40.568387
MonotonicityNot monotonic
2024-03-23T04:21:38.690245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 19
 
6.9%
90.0 6
 
2.2%
89.0 6
 
2.2%
84.9 5
 
1.8%
86.7 5
 
1.8%
91.1 5
 
1.8%
86.3 4
 
1.4%
87.2 4
 
1.4%
89.3 3
 
1.1%
91.7 3
 
1.1%
Other values (140) 217
78.3%
ValueCountFrequency (%)
66.0 1
0.4%
67.9 1
0.4%
70.3 1
0.4%
70.6 1
0.4%
72.3 1
0.4%
75.4 1
0.4%
75.5 1
0.4%
76.2 1
0.4%
76.3 1
0.4%
76.5 1
0.4%
ValueCountFrequency (%)
100.0 19
6.9%
98.8 2
 
0.7%
98.1 1
 
0.4%
98.0 2
 
0.7%
97.6 3
 
1.1%
97.5 1
 
0.4%
97.2 1
 
0.4%
97.1 1
 
0.4%
96.9 1
 
0.4%
96.3 1
 
0.4%

청렴성
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.741155
Minimum74
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:39.460673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile83.18
Q188
median90.5
Q393.5
95-th percentile100
Maximum100
Range26
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation4.8488721
Coefficient of variation (CV)0.053436306
Kurtosis0.39353339
Mean90.741155
Median Absolute Deviation (MAD)2.8
Skewness-0.19201019
Sum25135.3
Variance23.511561
MonotonicityNot monotonic
2024-03-23T04:21:40.119224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 17
 
6.1%
90.0 8
 
2.9%
89.5 6
 
2.2%
90.3 6
 
2.2%
92.4 5
 
1.8%
92.3 5
 
1.8%
90.7 4
 
1.4%
89.8 4
 
1.4%
88.9 4
 
1.4%
91.4 4
 
1.4%
Other values (127) 214
77.3%
ValueCountFrequency (%)
74.0 1
0.4%
76.1 1
0.4%
78.1 1
0.4%
78.2 1
0.4%
78.4 1
0.4%
78.6 1
0.4%
80.0 1
0.4%
81.1 1
0.4%
81.5 1
0.4%
81.7 1
0.4%
ValueCountFrequency (%)
100.0 17
6.1%
99.6 1
 
0.4%
99.5 1
 
0.4%
99.4 1
 
0.4%
99.0 1
 
0.4%
98.6 1
 
0.4%
98.5 1
 
0.4%
98.0 2
 
0.7%
97.5 1
 
0.4%
97.1 1
 
0.4%

전문성
Real number (ℝ)

HIGH CORRELATION 

Distinct138
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.036823
Minimum66.8
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:40.893496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66.8
5-th percentile78.58
Q184.9
median87.8
Q391.4
95-th percentile100
Maximum100
Range33.2
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.8576608
Coefficient of variation (CV)0.066536485
Kurtosis0.41501891
Mean88.036823
Median Absolute Deviation (MAD)3.3
Skewness-0.069965728
Sum24386.2
Variance34.31219
MonotonicityNot monotonic
2024-03-23T04:21:41.614423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 16
 
5.8%
88.8 6
 
2.2%
86.8 6
 
2.2%
88.7 6
 
2.2%
86.2 5
 
1.8%
87.0 5
 
1.8%
85.8 4
 
1.4%
84.4 4
 
1.4%
93.1 4
 
1.4%
86.4 4
 
1.4%
Other values (128) 217
78.3%
ValueCountFrequency (%)
66.8 1
0.4%
70.0 1
0.4%
74.2 1
0.4%
75.1 1
0.4%
76.3 1
0.4%
77.0 1
0.4%
77.1 2
0.7%
77.3 1
0.4%
77.8 1
0.4%
78.1 1
0.4%
ValueCountFrequency (%)
100.0 16
5.8%
99.0 1
 
0.4%
98.8 2
 
0.7%
98.1 1
 
0.4%
97.9 1
 
0.4%
97.8 1
 
0.4%
97.6 1
 
0.4%
97.5 1
 
0.4%
96.7 1
 
0.4%
96.0 3
 
1.1%

공정성
Real number (ℝ)

HIGH CORRELATION 

Distinct140
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.667509
Minimum62
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:42.211938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile78.8
Q185.3
median88.6
Q391.9
95-th percentile100
Maximum100
Range38
Interquartile range (IQR)6.6

Descriptive statistics

Standard deviation5.9222155
Coefficient of variation (CV)0.066791269
Kurtosis1.2570808
Mean88.667509
Median Absolute Deviation (MAD)3.3
Skewness-0.347797
Sum24560.9
Variance35.072636
MonotonicityNot monotonic
2024-03-23T04:21:43.053160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 16
 
5.8%
91.7 6
 
2.2%
90.5 5
 
1.8%
90.0 5
 
1.8%
85.3 5
 
1.8%
87.4 4
 
1.4%
85.1 4
 
1.4%
90.2 4
 
1.4%
87.0 4
 
1.4%
88.1 4
 
1.4%
Other values (130) 220
79.4%
ValueCountFrequency (%)
62.0 1
0.4%
67.7 1
0.4%
75.4 1
0.4%
75.5 1
0.4%
76.2 1
0.4%
76.7 1
0.4%
76.8 1
0.4%
77.9 1
0.4%
78.2 1
0.4%
78.5 1
0.4%
ValueCountFrequency (%)
100.0 16
5.8%
99.5 1
 
0.4%
98.8 3
 
1.1%
98.1 1
 
0.4%
97.9 1
 
0.4%
97.6 1
 
0.4%
97.2 1
 
0.4%
97.1 1
 
0.4%
97.0 1
 
0.4%
96.8 1
 
0.4%

편리성
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.042238
Minimum68
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T04:21:43.695969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68
5-th percentile78.68
Q184.8
median87.9
Q391.3
95-th percentile97.62
Maximum100
Range32
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.5862006
Coefficient of variation (CV)0.063449098
Kurtosis0.35083782
Mean88.042238
Median Absolute Deviation (MAD)3.2
Skewness-0.11233425
Sum24387.7
Variance31.205637
MonotonicityNot monotonic
2024-03-23T04:21:44.283633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 10
 
3.6%
87.5 7
 
2.5%
87.9 6
 
2.2%
93.3 5
 
1.8%
84.7 5
 
1.8%
85.7 5
 
1.8%
85.6 5
 
1.8%
89.3 4
 
1.4%
90.0 4
 
1.4%
90.3 4
 
1.4%
Other values (134) 222
80.1%
ValueCountFrequency (%)
68.0 1
 
0.4%
70.3 1
 
0.4%
74.4 1
 
0.4%
77.3 1
 
0.4%
77.4 1
 
0.4%
77.5 2
0.7%
77.9 2
0.7%
78.1 1
 
0.4%
78.5 1
 
0.4%
78.6 3
1.1%
ValueCountFrequency (%)
100.0 10
3.6%
99.6 1
 
0.4%
98.9 1
 
0.4%
97.9 1
 
0.4%
97.7 1
 
0.4%
97.6 1
 
0.4%
97.5 1
 
0.4%
97.2 1
 
0.4%
97.1 1
 
0.4%
97.0 1
 
0.4%

Interactions

2024-03-23T04:21:19.472161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:13.238541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:18.667398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:23.651034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:28.336317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:34.568408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:39.863847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:45.025987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:48.985288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:52.970077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:57.026778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:04.478644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:09.060326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:13.377744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:19.867539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:13.873055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:19.198798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:23.951682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:28.751513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:35.009685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:40.236948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:45.322821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:49.239743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:53.230231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:57.355669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:04.722127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:09.380870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:13.704345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:20.107748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:14.209980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:19.503069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:24.266824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:29.150681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:35.413566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:40.562054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:45.580614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:49.477551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:53.475729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:57.710936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:05.182644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:09.624433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:14.039191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:20.483593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:14.458907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:19.898980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:24.649329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:29.517624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:36.220409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:40.837222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:45.838134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:49.756504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:53.746598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:58.138418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:05.557832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:09.887999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:14.387031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:20.841227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:14.838850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:20.279023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:24.963181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:29.911663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:36.579128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:41.343867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:46.090558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:50.060062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:54.025379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:59.032368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:05.868690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:10.227754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:15.160925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:21.204599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:15.194373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:20.646596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:25.378374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:30.391264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:36.960922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:41.751321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:46.430695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:50.391939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:54.516025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:59.873708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:06.224918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:10.506974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:15.624791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:21.561915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:15.567184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:20.928173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:25.713443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:31.159508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:37.302409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:42.059857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:46.703055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:50.704131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:54.787033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:00.659659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:06.683294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:10.772965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:16.184202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:21.867410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:15.952241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:21.290578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:26.005043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:31.723623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:37.657077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:42.433923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:46.966131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:50.957049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:55.056155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:01.654554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:06.995615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:11.086354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:16.644000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:22.261656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:16.271760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:21.683785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:26.301504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:32.086158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:37.981396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:42.803880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:47.216722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:51.287604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:55.369817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:02.047539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:07.267654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:11.387406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:17.035258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:22.532881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:16.699917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:21.995151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:26.658911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:32.703270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:38.275988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:43.178200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:47.506258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:51.671534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:55.644746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:02.636774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:07.543265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:11.842462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:17.421352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:22.842390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:17.010092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:22.369460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:27.021572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:33.126359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:38.550942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:43.502897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:47.786472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:51.929398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:55.914400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:02.991430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:07.971994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:12.132728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:17.833579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:23.119631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:17.392134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:22.674078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:27.278307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:33.444771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:38.897260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:43.755753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:48.039271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:52.170800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:56.170865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:03.411645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:08.233520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:12.390533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:18.206471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:23.470770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:17.713279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:22.982654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:27.677027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:33.728791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:39.172934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:44.162034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:48.305068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:52.426100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:56.488598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:03.868892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:08.512229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:12.713490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:18.621744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:23.751478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:18.069599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:23.323354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:27.994167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:34.167462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:39.498151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:44.515462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:48.597629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:52.722279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:20:56.766522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:04.229303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:08.773288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:13.011955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:21:19.050406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T04:21:44.681197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.9640.9840.9480.9410.9020.8750.9230.8610.9640.9140.8860.8990.875
전반적만족도0.9641.0000.9670.9620.9460.9110.8700.9730.8870.9610.9140.9030.9080.870
요소만족도0.9840.9671.0000.9600.9710.9260.8640.9460.8970.9750.9500.9250.8970.864
업무처리 절차 및 과정0.9480.9620.9601.0000.9430.8780.8050.9760.9510.9530.9120.8710.8950.805
담당자응대태도0.9410.9460.9710.9431.0000.9260.8050.9300.8900.9890.9790.9240.9040.805
서비스품질0.9020.9110.9260.8780.9261.0000.9210.8610.9650.9230.8940.9890.9730.921
시설 및 이용환경0.8750.8700.8640.8050.8050.9211.0000.8300.9100.8170.7530.9340.9101.000
신속성0.9230.9730.9460.9760.9300.8610.8301.0000.8790.9430.8990.8460.8860.830
지원성0.8610.8870.8970.9510.8900.9650.9100.8791.0000.9110.8310.9590.9520.910
성실성0.9640.9610.9750.9530.9890.9230.8170.9430.9111.0000.9540.9120.9070.817
청렴성0.9140.9140.9500.9120.9790.8940.7530.8990.8310.9541.0000.8810.8880.753
전문성0.8860.9030.9250.8710.9240.9890.9340.8460.9590.9120.8811.0000.9640.934
공정성0.8990.9080.8970.8950.9040.9730.9100.8860.9520.9070.8880.9641.0000.910
편리성0.8750.8700.8640.8050.8050.9211.0000.8300.9100.8170.7530.9340.9101.000
2024-03-23T04:21:45.240850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.9780.9920.9520.9640.9770.9410.9320.9470.9670.9270.9690.9660.941
전반적만족도0.9781.0000.9740.9490.9220.9470.9150.9350.9320.9280.8840.9350.9400.915
요소만족도0.9920.9741.0000.9640.9670.9760.9420.9430.9590.9680.9330.9710.9630.942
업무처리 절차 및 과정0.9520.9490.9641.0000.9060.9160.8660.9880.9800.9210.8580.9110.9050.866
담당자응대태도0.9640.9220.9670.9061.0000.9690.8890.8780.9220.9870.9800.9710.9500.889
서비스품질0.9770.9470.9760.9160.9691.0000.9100.8930.9260.9660.9410.9890.9900.910
시설 및 이용환경0.9410.9150.9420.8660.8890.9101.0000.8440.8620.8930.8570.9050.8981.000
신속성0.9320.9350.9430.9880.8780.8930.8441.0000.9410.8930.8310.8900.8810.844
지원성0.9470.9320.9590.9800.9220.9260.8620.9411.0000.9360.8750.9210.9160.862
성실성0.9670.9280.9680.9210.9870.9660.8930.8930.9361.0000.9370.9660.9480.893
청렴성0.9270.8840.9330.8580.9800.9410.8570.8310.8750.9371.0000.9440.9210.857
전문성0.9690.9350.9710.9110.9710.9890.9050.8900.9210.9660.9441.0000.9610.905
공정성0.9660.9400.9630.9050.9500.9900.8980.8810.9160.9480.9210.9611.0000.898
편리성0.9410.9150.9420.8660.8890.9101.0000.8440.8620.8930.8570.9050.8981.000

Missing values

2024-03-23T04:21:24.211241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T04:21:24.932355image/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

응답자특성종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
0서울특별시경찰청82.279.383.480.785.284.183.780.381.282.587.883.784.583.7
1부산광역시경찰청88.386.689.187.390.689.688.787.487.289.092.289.090.388.7
2대구광역시경찰청84.982.785.884.086.886.086.783.584.485.188.485.986.186.7
3인천광역시경찰청86.183.887.084.688.387.487.984.085.386.790.087.487.387.9
4광주광역시경찰청89.687.790.489.691.490.889.790.189.289.893.090.291.389.7
5대전광역시경찰청87.385.788.085.989.689.087.584.986.988.191.288.889.287.5
6울산광역시경찰청86.384.387.284.789.088.187.084.484.987.290.987.988.487.0
7세종특별자치시경찰청82.579.683.880.884.983.386.479.282.383.086.983.882.786.4
8경기도남부경찰청80.677.282.079.284.282.881.878.879.581.686.982.583.281.8
9경기도북부경찰청86.083.687.184.888.487.487.984.485.286.790.087.587.487.9
응답자특성종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
267경남고성경찰서96.596.896.496.396.996.396.297.495.397.696.295.996.896.2
268하동경찰서94.293.394.693.195.594.595.291.494.892.498.693.895.295.2
269남해경찰서92.891.593.487.795.494.696.284.690.893.896.993.895.496.2
270함양경찰서97.498.899.399.4100.0100.097.598.8100.0100.0100.0100.0100.097.5
271산청경찰서89.587.390.586.495.091.489.185.587.393.696.492.790.089.1
272함안경찰서89.188.189.589.290.089.889.189.189.489.790.389.490.389.1
273의령경찰서94.4100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0
274제주동부경찰서87.285.587.985.789.388.787.985.086.487.591.288.788.787.9
275제주서부경찰서87.585.988.286.289.788.488.785.387.188.191.487.888.988.7
276서귀포경찰서89.988.590.589.491.890.490.588.590.391.192.490.090.890.5