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 수사분야 치안고객만족도(관서별) 분야(응답자 특성, 종합만족도, 전반적만족도, 요소만족도, 업무처리절차 및 과정, 담당자 응대 태도, 서비스 품질, 시설 및 이용환경, 신속성, 지원성, 성실성, 청렴성, 전문성, 공정성, 편리성)
Author경찰청
URLhttps://www.data.go.kr/data/15064409/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 06:50:22.957999
Analysis finished2024-03-23 06:51:39.292761
Duration1 minute and 16.33 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
2024-03-23T06:51:39.812251image/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%
2024-03-23T06:51:41.187676image/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 

Distinct138
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.820578
Minimum54.1
Maximum82.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:41.670265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54.1
5-th percentile59.54
Q164.7
median67.9
Q370.6
95-th percentile76.4
Maximum82.8
Range28.7
Interquartile range (IQR)5.9

Descriptive statistics

Standard deviation5.0750857
Coefficient of variation (CV)0.07483106
Kurtosis0.5006592
Mean67.820578
Median Absolute Deviation (MAD)3
Skewness-0.046173555
Sum18786.3
Variance25.756495
MonotonicityNot monotonic
2024-03-23T06:51:42.135611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69.3 6
 
2.2%
65.4 5
 
1.8%
67.1 5
 
1.8%
62.9 5
 
1.8%
65.6 5
 
1.8%
69.7 5
 
1.8%
66.9 4
 
1.4%
64.3 4
 
1.4%
71.6 4
 
1.4%
69.9 4
 
1.4%
Other values (128) 230
83.0%
ValueCountFrequency (%)
54.1 1
0.4%
54.3 1
0.4%
54.6 1
0.4%
54.8 1
0.4%
55.1 1
0.4%
56.6 2
0.7%
56.8 2
0.7%
57.6 1
0.4%
58.1 1
0.4%
58.2 1
0.4%
ValueCountFrequency (%)
82.8 1
0.4%
82.4 1
0.4%
82.1 1
0.4%
79.2 1
0.4%
78.8 1
0.4%
78.5 1
0.4%
78.3 1
0.4%
78.0 1
0.4%
77.8 2
0.7%
77.4 1
0.4%

전반적만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct162
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.956679
Minimum36
Maximum95.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:42.676099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile49.94
Q158.7
median63.1
Q366.7
95-th percentile74.38
Maximum95.3
Range59.3
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.8498223
Coefficient of variation (CV)0.12468609
Kurtosis2.5718855
Mean62.956679
Median Absolute Deviation (MAD)3.8
Skewness0.10064696
Sum17439
Variance61.619711
MonotonicityNot monotonic
2024-03-23T06:51:43.503761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62.6 6
 
2.2%
62.4 6
 
2.2%
67.0 5
 
1.8%
63.8 5
 
1.8%
65.2 4
 
1.4%
65.5 4
 
1.4%
66.4 4
 
1.4%
60.2 4
 
1.4%
64.3 4
 
1.4%
56.8 4
 
1.4%
Other values (152) 231
83.4%
ValueCountFrequency (%)
36.0 2
0.7%
40.6 1
0.4%
42.0 1
0.4%
43.1 1
0.4%
44.0 1
0.4%
44.4 1
0.4%
45.2 1
0.4%
48.8 1
0.4%
49.0 1
0.4%
49.2 1
0.4%
ValueCountFrequency (%)
95.3 1
0.4%
91.8 1
0.4%
90.5 1
0.4%
82.4 1
0.4%
81.0 1
0.4%
80.0 1
0.4%
79.7 1
0.4%
79.3 1
0.4%
77.4 1
0.4%
76.5 1
0.4%

요소만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct157
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.63935
Minimum39
Maximum94.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:44.059149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile58.64
Q166.5
median69.9
Q373
95-th percentile78.78
Maximum94.9
Range55.9
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation6.681247
Coefficient of variation (CV)0.095940686
Kurtosis3.4887079
Mean69.63935
Median Absolute Deviation (MAD)3.2
Skewness-0.1816596
Sum19290.1
Variance44.639062
MonotonicityNot monotonic
2024-03-23T06:51:44.477139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.8 7
 
2.5%
73.0 7
 
2.5%
72.5 6
 
2.2%
70.3 5
 
1.8%
69.5 5
 
1.8%
73.9 5
 
1.8%
67.8 4
 
1.4%
71.9 4
 
1.4%
68.2 4
 
1.4%
70.7 4
 
1.4%
Other values (147) 226
81.6%
ValueCountFrequency (%)
39.0 1
0.4%
47.2 1
0.4%
47.9 1
0.4%
49.4 1
0.4%
52.5 1
0.4%
56.2 1
0.4%
56.7 2
0.7%
56.8 1
0.4%
57.0 1
0.4%
57.1 1
0.4%
ValueCountFrequency (%)
94.9 1
0.4%
92.9 1
0.4%
92.5 1
0.4%
88.9 1
0.4%
88.8 1
0.4%
85.2 1
0.4%
84.1 1
0.4%
82.3 2
0.7%
80.3 1
0.4%
79.6 1
0.4%

업무처리 절차 및 과정
Real number (ℝ)

HIGH CORRELATION 

Distinct163
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.719134
Minimum34.5
Maximum92.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:45.026775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.5
5-th percentile52.1
Q160.2
median63.8
Q367.3
95-th percentile73.84
Maximum92.3
Range57.8
Interquartile range (IQR)7.1

Descriptive statistics

Standard deviation7.1286187
Coefficient of variation (CV)0.11187564
Kurtosis2.6998298
Mean63.719134
Median Absolute Deviation (MAD)3.6
Skewness0.084903776
Sum17650.2
Variance50.817205
MonotonicityNot monotonic
2024-03-23T06:51:45.649071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63.2 7
 
2.5%
64.6 6
 
2.2%
61.8 6
 
2.2%
61.2 4
 
1.4%
66.8 4
 
1.4%
64.3 4
 
1.4%
63.3 4
 
1.4%
64.1 4
 
1.4%
63.5 4
 
1.4%
64.4 4
 
1.4%
Other values (153) 230
83.0%
ValueCountFrequency (%)
34.5 1
0.4%
40.0 1
0.4%
44.6 1
0.4%
46.8 1
0.4%
48.5 1
0.4%
48.9 1
0.4%
49.5 1
0.4%
49.6 2
0.7%
49.8 1
0.4%
50.3 1
0.4%
ValueCountFrequency (%)
92.3 1
0.4%
90.2 1
0.4%
87.0 1
0.4%
84.0 1
0.4%
83.0 1
0.4%
78.9 1
0.4%
78.3 1
0.4%
77.6 1
0.4%
77.4 1
0.4%
76.9 1
0.4%

담당자응대태도
Real number (ℝ)

HIGH CORRELATION 

Distinct156
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.308664
Minimum40
Maximum98.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:46.461159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile60.98
Q169.1
median72.5
Q375.6
95-th percentile82.42
Maximum98.7
Range58.7
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation7.1153129
Coefficient of variation (CV)0.098401941
Kurtosis3.767566
Mean72.308664
Median Absolute Deviation (MAD)3.3
Skewness-0.3930268
Sum20029.5
Variance50.627678
MonotonicityNot monotonic
2024-03-23T06:51:47.049858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.4 5
 
1.8%
80.2 5
 
1.8%
73.0 5
 
1.8%
73.3 5
 
1.8%
69.8 4
 
1.4%
71.7 4
 
1.4%
71.6 4
 
1.4%
75.3 4
 
1.4%
74.1 4
 
1.4%
72.5 4
 
1.4%
Other values (146) 233
84.1%
ValueCountFrequency (%)
40.0 1
0.4%
45.6 1
0.4%
46.3 1
0.4%
49.5 1
0.4%
53.5 1
0.4%
54.3 1
0.4%
56.1 1
0.4%
57.9 1
0.4%
58.2 1
0.4%
59.1 1
0.4%
ValueCountFrequency (%)
98.7 1
0.4%
96.7 1
0.4%
94.5 1
0.4%
90.9 1
0.4%
90.8 1
0.4%
89.5 1
0.4%
89.2 1
0.4%
86.3 1
0.4%
84.0 1
0.4%
83.7 1
0.4%

서비스품질
Real number (ℝ)

HIGH CORRELATION 

Distinct159
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.777256
Minimum38
Maximum95.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:47.753947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile55.12
Q164.6
median68.1
Q371.1
95-th percentile78.42
Maximum95.3
Range57.3
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation7.3853917
Coefficient of variation (CV)0.10896563
Kurtosis3.004502
Mean67.777256
Median Absolute Deviation (MAD)3.5
Skewness-0.29157797
Sum18774.3
Variance54.54401
MonotonicityNot monotonic
2024-03-23T06:51:48.399273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.9 6
 
2.2%
67.7 6
 
2.2%
68.4 5
 
1.8%
70.8 4
 
1.4%
68.3 4
 
1.4%
61.4 4
 
1.4%
71.1 4
 
1.4%
70.3 4
 
1.4%
67.3 4
 
1.4%
72.2 4
 
1.4%
Other values (149) 232
83.8%
ValueCountFrequency (%)
38.0 1
0.4%
39.3 1
0.4%
43.5 1
0.4%
46.4 1
0.4%
48.5 1
0.4%
49.3 1
0.4%
50.5 1
0.4%
51.2 1
0.4%
53.0 1
0.4%
53.5 2
0.7%
ValueCountFrequency (%)
95.3 1
0.4%
91.5 1
0.4%
91.0 1
0.4%
88.8 1
0.4%
88.0 1
0.4%
84.0 1
0.4%
83.9 1
0.4%
81.5 1
0.4%
80.5 1
0.4%
80.4 1
0.4%

시설 및 이용환경
Real number (ℝ)

HIGH CORRELATION 

Distinct152
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.792419
Minimum38
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:48.944920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile66.18
Q173.2
median76.1
Q379.1
95-th percentile84.8
Maximum100
Range62
Interquartile range (IQR)5.9

Descriptive statistics

Standard deviation6.3132579
Coefficient of variation (CV)0.083296693
Kurtosis5.4369784
Mean75.792419
Median Absolute Deviation (MAD)2.9
Skewness-0.52036736
Sum20994.5
Variance39.857225
MonotonicityNot monotonic
2024-03-23T06:51:49.499298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76.1 9
 
3.2%
75.4 6
 
2.2%
79.6 5
 
1.8%
75.3 5
 
1.8%
76.5 5
 
1.8%
73.5 5
 
1.8%
77.4 5
 
1.8%
75.7 4
 
1.4%
77.0 4
 
1.4%
76.8 4
 
1.4%
Other values (142) 225
81.2%
ValueCountFrequency (%)
38.0 1
0.4%
58.0 1
0.4%
59.7 1
0.4%
60.0 1
0.4%
62.5 2
0.7%
63.0 1
0.4%
63.6 1
0.4%
64.0 2
0.7%
64.5 1
0.4%
65.7 1
0.4%
ValueCountFrequency (%)
100.0 1
0.4%
98.0 1
0.4%
95.3 1
0.4%
91.8 1
0.4%
89.5 1
0.4%
88.3 1
0.4%
87.9 1
0.4%
87.6 1
0.4%
87.0 2
0.7%
86.5 1
0.4%

신속성
Real number (ℝ)

HIGH CORRELATION 

Distinct166
Distinct (%)59.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.179422
Minimum33
Maximum90.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:50.035574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile50.14
Q158.9
median62.3
Q366.2
95-th percentile72.96
Maximum90.7
Range57.7
Interquartile range (IQR)7.3

Descriptive statistics

Standard deviation7.4244974
Coefficient of variation (CV)0.11940441
Kurtosis2.4297043
Mean62.179422
Median Absolute Deviation (MAD)3.6
Skewness-0.13655001
Sum17223.7
Variance55.123162
MonotonicityNot monotonic
2024-03-23T06:51:50.572747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61.2 5
 
1.8%
66.6 5
 
1.8%
65.4 5
 
1.8%
59.8 5
 
1.8%
65.2 5
 
1.8%
61.0 4
 
1.4%
61.6 4
 
1.4%
59.5 4
 
1.4%
61.7 4
 
1.4%
64.8 4
 
1.4%
Other values (156) 232
83.8%
ValueCountFrequency (%)
33.0 1
0.4%
37.0 1
0.4%
40.0 1
0.4%
42.9 1
0.4%
43.8 1
0.4%
44.3 1
0.4%
45.7 1
0.4%
45.8 1
0.4%
45.9 1
0.4%
47.8 1
0.4%
ValueCountFrequency (%)
90.7 1
0.4%
89.4 1
0.4%
84.8 1
0.4%
82.0 1
0.4%
78.8 1
0.4%
77.2 1
0.4%
76.6 1
0.4%
75.2 1
0.4%
75.0 1
0.4%
74.7 1
0.4%

지원성
Real number (ℝ)

HIGH CORRELATION 

Distinct166
Distinct (%)59.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.254874
Minimum36
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:51.106132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile54.8
Q161.1
median65.3
Q368.6
95-th percentile76.48
Maximum94
Range58
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation7.2211811
Coefficient of variation (CV)0.11066118
Kurtosis3.0021237
Mean65.254874
Median Absolute Deviation (MAD)3.5
Skewness0.28247663
Sum18075.6
Variance52.145456
MonotonicityNot monotonic
2024-03-23T06:51:51.588331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63.7 5
 
1.8%
63.5 5
 
1.8%
66.8 5
 
1.8%
64.4 4
 
1.4%
65.6 4
 
1.4%
63.0 4
 
1.4%
68.6 4
 
1.4%
64.7 4
 
1.4%
54.8 4
 
1.4%
61.0 4
 
1.4%
Other values (156) 234
84.5%
ValueCountFrequency (%)
36.0 1
0.4%
40.0 1
0.4%
46.3 1
0.4%
47.7 1
0.4%
49.9 1
0.4%
51.1 1
0.4%
51.5 1
0.4%
51.6 1
0.4%
52.7 1
0.4%
53.0 1
0.4%
ValueCountFrequency (%)
94.0 1
0.4%
92.0 1
0.4%
91.0 1
0.4%
88.8 1
0.4%
84.0 1
0.4%
83.2 1
0.4%
80.8 1
0.4%
80.0 1
0.4%
79.7 1
0.4%
79.0 1
0.4%

성실성
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.609025
Minimum36
Maximum97.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:52.153548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile56.8
Q164.5
median68.8
Q372.4
95-th percentile79.12
Maximum97.4
Range61.4
Interquartile range (IQR)7.9

Descriptive statistics

Standard deviation7.7010698
Coefficient of variation (CV)0.11224573
Kurtosis3.3396585
Mean68.609025
Median Absolute Deviation (MAD)3.8
Skewness-0.093351062
Sum19004.7
Variance59.306476
MonotonicityNot monotonic
2024-03-23T06:51:52.862496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.0 8
 
2.9%
66.9 5
 
1.8%
70.6 5
 
1.8%
68.7 5
 
1.8%
67.3 4
 
1.4%
66.3 4
 
1.4%
68.9 4
 
1.4%
63.5 4
 
1.4%
68.4 4
 
1.4%
73.0 3
 
1.1%
Other values (157) 231
83.4%
ValueCountFrequency (%)
36.0 1
0.4%
40.0 1
0.4%
44.9 1
0.4%
45.8 1
0.4%
47.0 1
0.4%
50.2 1
0.4%
51.9 1
0.4%
53.3 1
0.4%
53.8 1
0.4%
54.0 1
0.4%
ValueCountFrequency (%)
97.4 1
0.4%
96.7 1
0.4%
94.0 1
0.4%
90.0 1
0.4%
89.0 1
0.4%
88.0 2
0.7%
85.3 1
0.4%
84.3 1
0.4%
83.6 1
0.4%
81.1 1
0.4%

청렴성
Real number (ℝ)

HIGH CORRELATION 

Distinct160
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.005415
Minimum40
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:53.392904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile64.52
Q173.1
median76.3
Q379.3
95-th percentile86.32
Maximum100
Range60
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation7.0182428
Coefficient of variation (CV)0.09233872
Kurtosis4.9344832
Mean76.005415
Median Absolute Deviation (MAD)3.2
Skewness-0.84611488
Sum21053.5
Variance49.255731
MonotonicityNot monotonic
2024-03-23T06:51:53.976700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.0 7
 
2.5%
77.5 6
 
2.2%
76.5 6
 
2.2%
75.8 6
 
2.2%
76.3 5
 
1.8%
77.7 4
 
1.4%
76.1 4
 
1.4%
77.8 4
 
1.4%
72.0 4
 
1.4%
73.1 4
 
1.4%
Other values (150) 227
81.9%
ValueCountFrequency (%)
40.0 1
0.4%
45.4 1
0.4%
47.7 1
0.4%
55.3 1
0.4%
57.6 1
0.4%
60.0 2
0.7%
60.4 1
0.4%
60.5 1
0.4%
62.0 1
0.4%
62.8 1
0.4%
ValueCountFrequency (%)
100.0 1
0.4%
96.7 1
0.4%
95.0 1
0.4%
93.7 1
0.4%
92.6 1
0.4%
91.8 1
0.4%
90.7 1
0.4%
90.4 1
0.4%
90.0 1
0.4%
88.9 1
0.4%

전문성
Real number (ℝ)

HIGH CORRELATION 

Distinct170
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.491697
Minimum38
Maximum94.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:54.572351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile54.86
Q164
median67.7
Q371.4
95-th percentile78.44
Maximum94.7
Range56.7
Interquartile range (IQR)7.4

Descriptive statistics

Standard deviation7.5912542
Coefficient of variation (CV)0.11247686
Kurtosis2.7873798
Mean67.491697
Median Absolute Deviation (MAD)3.7
Skewness-0.30292531
Sum18695.2
Variance57.627141
MonotonicityNot monotonic
2024-03-23T06:51:55.342320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68.9 5
 
1.8%
67.2 5
 
1.8%
69.8 5
 
1.8%
66.8 4
 
1.4%
73.9 4
 
1.4%
67.3 4
 
1.4%
66.1 4
 
1.4%
64.4 4
 
1.4%
67.4 4
 
1.4%
71.4 4
 
1.4%
Other values (160) 234
84.5%
ValueCountFrequency (%)
38.0 1
0.4%
40.0 1
0.4%
42.0 1
0.4%
43.6 1
0.4%
46.2 1
0.4%
49.6 1
0.4%
49.9 1
0.4%
50.3 1
0.4%
51.0 1
0.4%
51.3 1
0.4%
ValueCountFrequency (%)
94.7 1
0.4%
93.0 1
0.4%
90.2 1
0.4%
89.0 1
0.4%
88.2 1
0.4%
86.3 1
0.4%
83.1 1
0.4%
82.0 1
0.4%
80.5 1
0.4%
80.0 1
0.4%

공정성
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.068231
Minimum35
Maximum96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:55.871473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile55.98
Q165
median68.3
Q371.3
95-th percentile78.84
Maximum96
Range61
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation7.4158957
Coefficient of variation (CV)0.10894797
Kurtosis3.7784853
Mean68.068231
Median Absolute Deviation (MAD)3.2
Skewness-0.40509489
Sum18854.9
Variance54.995509
MonotonicityNot monotonic
2024-03-23T06:51:56.285473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69.3 6
 
2.2%
68.3 5
 
1.8%
71.3 5
 
1.8%
67.5 5
 
1.8%
67.4 5
 
1.8%
68.2 5
 
1.8%
70.1 4
 
1.4%
70.2 4
 
1.4%
69.0 4
 
1.4%
62.1 4
 
1.4%
Other values (157) 230
83.0%
ValueCountFrequency (%)
35.0 1
0.4%
36.0 1
0.4%
43.1 1
0.4%
49.0 1
0.4%
49.2 1
0.4%
50.8 1
0.4%
51.0 1
0.4%
52.3 1
0.4%
52.9 1
0.4%
53.2 1
0.4%
ValueCountFrequency (%)
96.0 1
0.4%
93.9 1
0.4%
90.0 1
0.4%
87.4 1
0.4%
87.0 1
0.4%
84.6 1
0.4%
83.2 1
0.4%
81.7 1
0.4%
81.3 1
0.4%
81.0 2
0.7%

편리성
Real number (ℝ)

HIGH CORRELATION 

Distinct152
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.792419
Minimum38
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-23T06:51:56.848698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile66.18
Q173.2
median76.1
Q379.1
95-th percentile84.8
Maximum100
Range62
Interquartile range (IQR)5.9

Descriptive statistics

Standard deviation6.3132579
Coefficient of variation (CV)0.083296693
Kurtosis5.4369784
Mean75.792419
Median Absolute Deviation (MAD)2.9
Skewness-0.52036736
Sum20994.5
Variance39.857225
MonotonicityNot monotonic
2024-03-23T06:51:57.275864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76.1 9
 
3.2%
75.4 6
 
2.2%
79.6 5
 
1.8%
75.3 5
 
1.8%
76.5 5
 
1.8%
73.5 5
 
1.8%
77.4 5
 
1.8%
75.7 4
 
1.4%
77.0 4
 
1.4%
76.8 4
 
1.4%
Other values (142) 225
81.2%
ValueCountFrequency (%)
38.0 1
0.4%
58.0 1
0.4%
59.7 1
0.4%
60.0 1
0.4%
62.5 2
0.7%
63.0 1
0.4%
63.6 1
0.4%
64.0 2
0.7%
64.5 1
0.4%
65.7 1
0.4%
ValueCountFrequency (%)
100.0 1
0.4%
98.0 1
0.4%
95.3 1
0.4%
91.8 1
0.4%
89.5 1
0.4%
88.3 1
0.4%
87.9 1
0.4%
87.6 1
0.4%
87.0 2
0.7%
86.5 1
0.4%

Interactions

2024-03-23T06:51:32.491190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:25.013166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:30.120451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:35.192342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:40.348336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:45.472925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:51.447155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:57.153098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:02.167034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:07.622852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:12.423337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:17.237618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:22.188921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:27.273359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:32.829030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:25.454713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:30.473976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:35.456009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:40.707787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:45.759097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:51.820579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:57.499788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:02.551195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:07.984236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:12.758301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:17.496528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:22.577086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:27.628366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:33.224199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:25.782835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:30.804421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:35.831919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:41.024288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:46.175152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:52.259919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:57.881844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:02.977208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:08.359549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:13.115978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:17.876839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:22.934273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:28.100199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:33.608588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:26.178060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:31.120011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:36.342127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:41.355705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:46.743548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:52.862264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:58.199472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:03.327443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:08.801255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:13.464591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:18.212850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:23.448627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:28.481957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:33.930373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:26.514962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:31.459138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:36.692720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:41.742869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:47.157881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:53.121772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:58.567648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:03.680265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:09.202635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:13.878604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:18.572392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:23.872934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:28.866269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:34.196912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:26.930935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:31.807898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:36.970399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:42.138252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:47.677476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:53.606483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:59.142351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:04.055968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:09.526574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:14.252761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:18.833799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:24.196755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:29.233629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:34.597738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:27.297096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:32.148777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:37.424221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:42.693685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:48.121707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:53.976960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:59.457009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:04.379361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:09.925829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:14.589546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:19.071601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:24.555454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:29.769064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:34.915384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:27.722738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:32.568110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:37.773103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:43.088115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:48.566452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:54.323405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:59.881687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:04.820861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:10.186533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:14.972065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:19.402308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:24.882741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:30.252993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:35.220788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:28.014857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:32.851264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:38.075557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:43.445464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:48.854102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:54.634170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:00.183877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:05.193096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:10.535576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:15.321835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:19.739038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:25.145636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:30.568353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:35.594308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:28.279837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:33.216820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:38.521293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:43.774333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:49.235911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:55.074985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:00.555456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:05.566793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:10.875437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:15.587780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:20.023926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:25.398587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:30.907460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:35.976521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:28.590165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:33.510795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:38.939292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:44.144081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:49.838884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:55.514605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:00.909718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:06.106195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:11.243004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:15.858767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:20.416998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:25.845438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:31.212900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:36.400132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:29.063760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:33.835008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:39.326951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:44.478899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:50.295976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:55.992777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:01.270185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:06.500220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:11.550344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:16.197593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:20.835958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:26.235456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:31.479200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:36.904236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:29.420619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:34.536438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:39.674890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:44.722547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:50.615361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:56.316723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:01.577475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:06.928136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:11.846559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:16.474005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:21.397041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:26.519511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:31.804994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:37.425137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:29.769395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:34.842238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:40.083811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:45.100445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:51.088662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:50:56.853960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:01.831470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:07.285230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:12.117117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:16.885723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:21.795866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:26.810283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:51:32.202979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:51:58.277399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.8110.9140.9060.8700.8910.6950.8750.8750.8900.8150.9060.9070.695
전반적만족도0.8111.0000.8830.8830.8620.8890.7580.8120.8590.8810.8420.8650.8610.758
요소만족도0.9140.8831.0000.9500.9810.9790.8950.9060.9560.9780.9510.9500.9780.895
업무처리 절차 및 과정0.9060.8830.9501.0000.9340.9460.7910.9710.9860.9580.9080.9360.9400.791
담당자응대태도0.8700.8620.9810.9341.0000.9650.8310.8990.9500.9760.9740.9390.9730.831
서비스품질0.8910.8890.9790.9460.9651.0000.8490.8960.9580.9790.9490.9840.9800.849
시설 및 이용환경0.6950.7580.8950.7910.8310.8491.0000.7020.8320.8460.8320.7370.8421.000
신속성0.8750.8120.9060.9710.8990.8960.7021.0000.9340.8940.8750.9180.9160.702
지원성0.8750.8590.9560.9860.9500.9580.8320.9341.0000.9680.9210.9480.9350.832
성실성0.8900.8810.9780.9580.9760.9790.8460.8940.9681.0000.9420.9520.9560.846
청렴성0.8150.8420.9510.9080.9740.9490.8320.8750.9210.9421.0000.9130.9720.832
전문성0.9060.8650.9500.9360.9390.9840.7370.9180.9480.9520.9131.0000.9370.737
공정성0.9070.8610.9780.9400.9730.9800.8420.9160.9350.9560.9720.9371.0000.842
편리성0.6950.7580.8950.7910.8310.8491.0000.7020.8320.8460.8320.7370.8421.000
2024-03-23T06:51:58.796444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
종합만족도1.0000.9290.9430.9150.8910.9150.7880.8760.8990.9070.8020.9070.8870.788
전반적만족도0.9291.0000.9460.9320.8850.9270.7660.8950.9080.9140.7910.9180.8990.766
요소만족도0.9430.9461.0000.9480.9600.9710.8420.9020.9310.9630.8800.9590.9450.842
업무처리 절차 및 과정0.9150.9320.9481.0000.8840.9250.7330.9650.9670.9130.7870.9150.8950.733
담당자응대태도0.8910.8850.9600.8841.0000.9400.7550.8330.8730.9650.9520.9180.9290.755
서비스품질0.9150.9270.9710.9250.9401.0000.7430.8650.9210.9380.8700.9820.9770.743
시설 및 이용환경0.7880.7660.8420.7330.7550.7431.0000.7140.7140.7660.6880.7430.7231.000
신속성0.8760.8950.9020.9650.8330.8650.7141.0000.8750.8590.7450.8490.8470.714
지원성0.8990.9080.9310.9670.8730.9210.7140.8751.0000.9080.7710.9210.8820.714
성실성0.9070.9140.9630.9130.9650.9380.7660.8590.9081.0000.8470.9350.9060.766
청렴성0.8020.7910.8800.7870.9520.8700.6880.7450.7710.8471.0000.8300.8830.688
전문성0.9070.9180.9590.9150.9180.9820.7430.8490.9210.9350.8301.0000.9240.743
공정성0.8870.8990.9450.8950.9290.9770.7230.8470.8820.9060.8830.9241.0000.723
편리성0.7880.7660.8420.7330.7550.7431.0000.7140.7140.7660.6880.7430.7231.000

Missing values

2024-03-23T06:51:37.947706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:51:38.961652image/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
0서울특별시경찰청64.158.466.559.669.865.072.557.861.565.074.664.965.172.5
1부산광역시경찰청69.965.971.666.573.970.776.165.167.870.277.570.271.376.1
2대구광역시경찰청65.760.667.963.070.665.973.261.564.566.175.064.966.973.2
3인천광역시경찰청67.062.868.862.471.567.774.761.363.667.975.167.268.274.7
4광주광역시경찰청69.364.371.566.274.269.976.565.467.070.577.969.770.176.5
5대전광역시경찰청67.162.469.264.170.567.076.262.765.466.774.366.867.276.2
6울산광역시경찰청71.767.273.668.375.872.079.267.868.872.778.971.872.279.2
7세종특별자치시경찰청63.256.966.058.968.762.874.957.260.762.974.561.763.974.9
8경기도남부경찰청65.660.268.062.071.166.473.560.663.366.875.466.166.773.5
9경기도북부경찰청68.162.970.364.673.268.476.163.965.368.877.568.168.676.1
응답자특성종합만족도전반적만족도요소만족도업무처리 절차 및 과정담당자응대태도서비스품질시설 및 이용환경신속성지원성성실성청렴성전문성공정성편리성
267경남고성경찰서71.872.875.869.480.577.975.364.474.577.083.978.877.075.3
268하동경찰서71.669.578.773.880.879.980.769.378.279.782.080.579.380.7
269남해경찰서78.079.385.278.390.884.088.372.784.088.093.786.381.788.3
270함양경찰서62.552.966.653.873.665.175.451.356.367.379.959.470.775.4
271산청경찰서72.580.082.377.689.280.482.475.280.088.090.477.683.282.4
272함안경찰서68.462.870.863.875.468.176.963.763.874.576.267.369.076.9
273의령경찰서69.757.470.660.081.364.378.360.359.770.092.662.366.378.3
274제주동부경찰서70.666.572.467.076.570.476.465.568.672.880.269.571.376.4
275제주서부경찰서67.262.469.261.871.667.777.259.863.767.375.867.168.277.2
276서귀포경찰서65.660.467.861.071.464.775.458.963.166.975.963.965.675.4