Overview

Dataset statistics

Number of variables10
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory89.8 B

Variable types

Categorical3
Numeric7

Dataset

Description유가보조금관리시스템 사용자 만족도 현황으로,유가보조금관리시스템을 사용하는 사용자에게 매년 만족도 조사를 한 2017년부터 2023년 까지의 만족도 현황 정보 입니다.
Author국토교통부
URLhttps://www.data.go.kr/data/15072458/fileData.do

Alerts

평균점수 is highly overall correlated with 전체대상수 and 2 other fieldsHigh correlation
년도 is highly overall correlated with 전체대상수 and 2 other fieldsHigh correlation
전체대상수 is highly overall correlated with 응답인원수 and 2 other fieldsHigh correlation
응답인원수 is highly overall correlated with 전체대상수 and 2 other fieldsHigh correlation
매우 만족 is highly overall correlated with 보통High correlation
보통 is highly overall correlated with 매우 만족 and 1 other fieldsHigh correlation
불만족 is highly overall correlated with 보통High correlation
불만족 has 9 (12.9%) zerosZeros
매우 불만족 has 25 (35.7%) zerosZeros

Reproduction

Analysis started2024-03-15 00:33:40.052816
Analysis finished2024-03-15 00:33:53.239350
Duration13.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2023년
10 
2022년
10 
2021년
10 
2020년
10 
2019년
10 
Other values (2)
20 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023년
2nd row2023년
3rd row2023년
4th row2023년
5th row2023년

Common Values

ValueCountFrequency (%)
2023년 10
14.3%
2022년 10
14.3%
2021년 10
14.3%
2020년 10
14.3%
2019년 10
14.3%
2018년 10
14.3%
2017년 10
14.3%

Length

2024-03-15T09:33:53.457479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:33:53.814790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023년 10
14.3%
2022년 10
14.3%
2021년 10
14.3%
2020년 10
14.3%
2019년 10
14.3%
2018년 10
14.3%
2017년 10
14.3%

전체대상수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean591.42857
Minimum522
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:54.171170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum522
5-th percentile522
Q1581
median597
Q3620
95-th percentile630
Maximum630
Range108
Interquartile range (IQR)39

Descriptive statistics

Standard deviation32.614823
Coefficient of variation (CV)0.055145837
Kurtosis0.51643312
Mean591.42857
Median Absolute Deviation (MAD)16
Skewness-1.0935323
Sum41400
Variance1063.7267
MonotonicityNot monotonic
2024-03-15T09:33:54.500484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
590 10
14.3%
630 10
14.3%
600 10
14.3%
597 10
14.3%
620 10
14.3%
581 10
14.3%
522 10
14.3%
ValueCountFrequency (%)
522 10
14.3%
581 10
14.3%
590 10
14.3%
597 10
14.3%
600 10
14.3%
620 10
14.3%
630 10
14.3%
ValueCountFrequency (%)
630 10
14.3%
620 10
14.3%
600 10
14.3%
597 10
14.3%
590 10
14.3%
581 10
14.3%
522 10
14.3%

응답인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186.85714
Minimum164
Maximum210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:54.900499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum164
5-th percentile164
Q1179
median181
Q3201
95-th percentile210
Maximum210
Range46
Interquartile range (IQR)22

Descriptive statistics

Standard deviation14.319628
Coefficient of variation (CV)0.076634097
Kurtosis-0.85380814
Mean186.85714
Median Absolute Deviation (MAD)11
Skewness0.12861851
Sum13080
Variance205.05176
MonotonicityNot monotonic
2024-03-15T09:33:55.236928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
181 20
28.6%
192 10
14.3%
164 10
14.3%
179 10
14.3%
201 10
14.3%
210 10
14.3%
ValueCountFrequency (%)
164 10
14.3%
179 10
14.3%
181 20
28.6%
192 10
14.3%
201 10
14.3%
210 10
14.3%
ValueCountFrequency (%)
210 10
14.3%
201 10
14.3%
192 10
14.3%
181 20
28.6%
179 10
14.3%
164 10
14.3%

평균점수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size688.0 B
78
30 
82
20 
83
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row78
2nd row78
3rd row78
4th row78
5th row78

Common Values

ValueCountFrequency (%)
78 30
42.9%
82 20
28.6%
83 20
28.6%

Length

2024-03-15T09:33:55.623622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:33:55.979670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
78 30
42.9%
82 20
28.6%
83 20
28.6%

문항
Categorical

Distinct11
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size688.0 B
시스템 활용도
7 
시스템 제공 정보
7 
시스템 UI
7 
시스템 이용편의성
7 
시스템 운영자와 유선 연결
7 
Other values (6)
35 

Length

Max length25
Median length15
Mean length10.157143
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시스템 활용도
2nd row업무의 투명성 및 효율성 향상
3rd row시스템 제공 정보
4th row시스템 UI
5th row시스템 이용편의성

Common Values

ValueCountFrequency (%)
시스템 활용도 7
10.0%
시스템 제공 정보 7
10.0%
시스템 UI 7
10.0%
시스템 이용편의성 7
10.0%
시스템 운영자와 유선 연결 7
10.0%
시스템 운영자 태도 7
10.0%
민원처리시간 7
10.0%
민원처리결과 7
10.0%
시스템에 대한 전반적인 만족도 7
10.0%
업무의 투명성 및 효율성 향상 5
7.1%

Length

2024-03-15T09:33:56.369896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시스템 44
22.8%
민원처리결과 7
 
3.6%
향상 7
 
3.6%
효율성 7
 
3.6%
및 7
 
3.6%
투명성 7
 
3.6%
업무의 7
 
3.6%
만족도 7
 
3.6%
전반적인 7
 
3.6%
대한 7
 
3.6%
Other values (13) 86
44.6%

매우 만족
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.485714
Minimum31
Maximum127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:56.766437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile32
Q140
median66.5
Q383.5
95-th percentile103.1
Maximum127
Range96
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation25.107158
Coefficient of variation (CV)0.38934449
Kurtosis-1.0174866
Mean64.485714
Median Absolute Deviation (MAD)23.5
Skewness0.21801157
Sum4514
Variance630.36936
MonotonicityNot monotonic
2024-03-15T09:33:57.179443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
81 3
 
4.3%
32 3
 
4.3%
36 3
 
4.3%
33 3
 
4.3%
41 3
 
4.3%
72 3
 
4.3%
31 3
 
4.3%
50 2
 
2.9%
68 2
 
2.9%
104 2
 
2.9%
Other values (34) 43
61.4%
ValueCountFrequency (%)
31 3
4.3%
32 3
4.3%
33 3
4.3%
34 2
2.9%
35 1
 
1.4%
36 3
4.3%
37 2
2.9%
40 2
2.9%
41 3
4.3%
42 1
 
1.4%
ValueCountFrequency (%)
127 1
1.4%
109 1
1.4%
104 2
2.9%
102 1
1.4%
101 1
1.4%
98 2
2.9%
96 1
1.4%
95 1
1.4%
92 1
1.4%
91 1
1.4%

만족
Real number (ℝ)

Distinct44
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.885714
Minimum45
Maximum129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:57.413149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile50.9
Q170
median81
Q394.75
95-th percentile112
Maximum129
Range84
Interquartile range (IQR)24.75

Descriptive statistics

Standard deviation18.73348
Coefficient of variation (CV)0.22877592
Kurtosis-0.17215746
Mean81.885714
Median Absolute Deviation (MAD)11.5
Skewness0.19329216
Sum5732
Variance350.94327
MonotonicityNot monotonic
2024-03-15T09:33:57.699692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
86 4
 
5.7%
73 4
 
5.7%
70 3
 
4.3%
85 3
 
4.3%
74 3
 
4.3%
79 3
 
4.3%
95 3
 
4.3%
109 2
 
2.9%
90 2
 
2.9%
57 2
 
2.9%
Other values (34) 41
58.6%
ValueCountFrequency (%)
45 1
1.4%
47 2
2.9%
50 1
1.4%
52 1
1.4%
55 1
1.4%
56 1
1.4%
57 2
2.9%
60 1
1.4%
63 1
1.4%
65 2
2.9%
ValueCountFrequency (%)
129 1
1.4%
125 1
1.4%
116 1
1.4%
112 2
2.9%
109 2
2.9%
108 1
1.4%
106 1
1.4%
102 1
1.4%
101 1
1.4%
99 1
1.4%

보통
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.971429
Minimum7
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:58.024734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile12.35
Q119
median27.5
Q346.5
95-th percentile63.55
Maximum71
Range64
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.609733
Coefficient of variation (CV)0.5037614
Kurtosis-0.84556386
Mean32.971429
Median Absolute Deviation (MAD)10
Skewness0.55616044
Sum2308
Variance275.88323
MonotonicityNot monotonic
2024-03-15T09:33:58.343427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
17 5
 
7.1%
23 5
 
7.1%
18 4
 
5.7%
53 3
 
4.3%
22 3
 
4.3%
33 3
 
4.3%
24 3
 
4.3%
19 3
 
4.3%
56 3
 
4.3%
45 3
 
4.3%
Other values (30) 35
50.0%
ValueCountFrequency (%)
7 1
 
1.4%
8 1
 
1.4%
10 1
 
1.4%
11 1
 
1.4%
14 1
 
1.4%
15 1
 
1.4%
16 1
 
1.4%
17 5
7.1%
18 4
5.7%
19 3
4.3%
ValueCountFrequency (%)
71 1
 
1.4%
66 1
 
1.4%
64 2
2.9%
63 1
 
1.4%
58 1
 
1.4%
57 1
 
1.4%
56 3
4.3%
55 1
 
1.4%
53 3
4.3%
50 1
 
1.4%

불만족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6
Minimum0
Maximum15
Zeros9
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:58.573872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile13.55
Maximum15
Range15
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.521767
Coefficient of variation (CV)0.80745839
Kurtosis-0.92962597
Mean5.6
Median Absolute Deviation (MAD)3.5
Skewness0.52306238
Sum392
Variance20.446377
MonotonicityNot monotonic
2024-03-15T09:33:58.776212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 9
12.9%
7 7
10.0%
2 7
10.0%
1 7
10.0%
5 6
8.6%
3 6
8.6%
13 5
7.1%
4 4
 
5.7%
6 4
 
5.7%
14 3
 
4.3%
Other values (6) 12
17.1%
ValueCountFrequency (%)
0 9
12.9%
1 7
10.0%
2 7
10.0%
3 6
8.6%
4 4
5.7%
5 6
8.6%
6 4
5.7%
7 7
10.0%
8 1
 
1.4%
9 3
 
4.3%
ValueCountFrequency (%)
15 1
 
1.4%
14 3
4.3%
13 5
7.1%
12 2
 
2.9%
11 3
4.3%
10 2
 
2.9%
9 3
4.3%
8 1
 
1.4%
7 7
10.0%
6 4
5.7%

매우 불만족
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9142857
Minimum0
Maximum8
Zeros25
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-15T09:33:59.073481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q33
95-th percentile6.1
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0269407
Coefficient of variation (CV)1.0588496
Kurtosis0.69146583
Mean1.9142857
Median Absolute Deviation (MAD)1.5
Skewness1.055087
Sum134
Variance4.1084886
MonotonicityNot monotonic
2024-03-15T09:33:59.459900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 25
35.7%
2 11
15.7%
1 10
 
14.3%
4 9
 
12.9%
3 9
 
12.9%
7 3
 
4.3%
5 2
 
2.9%
8 1
 
1.4%
ValueCountFrequency (%)
0 25
35.7%
1 10
 
14.3%
2 11
15.7%
3 9
 
12.9%
4 9
 
12.9%
5 2
 
2.9%
7 3
 
4.3%
8 1
 
1.4%
ValueCountFrequency (%)
8 1
 
1.4%
7 3
 
4.3%
5 2
 
2.9%
4 9
 
12.9%
3 9
 
12.9%
2 11
15.7%
1 10
 
14.3%
0 25
35.7%

Interactions

2024-03-15T09:33:50.136424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:40.726190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:42.423783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:43.957888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:45.692873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.029970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:48.250276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:50.425841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:40.964922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:42.619591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:44.196449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:45.852692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.172921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:48.497234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:50.894511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:41.197789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:42.811456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:44.435846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:46.064466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.313008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:48.751956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:51.230449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:41.434094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:42.974817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:44.666663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:46.295069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.483913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:48.900223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:51.482097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:41.663076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:43.189923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:44.951416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:46.514750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.696401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:49.199282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:51.760958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:41.911307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:43.444167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:45.199015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:46.710388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:47.891597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:49.484071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:52.039735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:42.162027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:43.698518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:45.448461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:46.876415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:48.049486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:33:49.754777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:33:59.653048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도전체대상수응답인원수평균점수문항매우 만족만족보통불만족매우 불만족
년도1.0001.0001.0001.0000.0000.0000.0960.3130.0000.071
전체대상수1.0001.0000.7530.6340.0000.0000.0000.1910.0000.000
응답인원수1.0000.7531.0000.5850.0000.0920.0000.4580.1250.279
평균점수1.0000.6340.5851.0000.0000.0000.3060.3960.0000.000
문항0.0000.0000.0000.0001.0000.7780.6450.6410.5510.445
매우 만족0.0000.0000.0920.0000.7781.0000.6440.6930.6010.319
만족0.0960.0000.0000.3060.6450.6441.0000.2490.0000.000
보통0.3130.1910.4580.3960.6410.6930.2491.0000.7030.435
불만족0.0000.0000.1250.0000.5510.6010.0000.7031.0000.352
매우 불만족0.0710.0000.2790.0000.4450.3190.0000.4350.3521.000
2024-03-15T09:33:59.866534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평균점수년도문항
평균점수1.0000.9700.000
년도0.9701.0000.000
문항0.0000.0001.000
2024-03-15T09:34:00.137915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체대상수응답인원수매우 만족만족보통불만족매우 불만족년도평균점수문항
전체대상수1.000-0.523-0.048-0.343-0.0400.0270.2430.9840.7360.000
응답인원수-0.5231.0000.1070.4080.2530.1010.0210.9840.7160.000
매우 만족-0.0480.1071.000-0.432-0.716-0.496-0.2090.0000.0000.469
만족-0.3430.408-0.4321.0000.090-0.213-0.2430.0150.1770.335
보통-0.0400.253-0.7160.0901.0000.7660.3360.1530.2420.332
불만족0.0270.101-0.496-0.2130.7661.0000.4730.0000.0000.328
매우 불만족0.2430.021-0.209-0.2430.3360.4731.0000.0000.0000.218
년도0.9840.9840.0000.0150.1530.0000.0001.0000.9700.000
평균점수0.7360.7160.0000.1770.2420.0000.0000.9701.0000.000
문항0.0000.0000.4690.3350.3320.3280.2180.0000.0001.000

Missing values

2024-03-15T09:33:52.467723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:33:52.998361image/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

년도전체대상수응답인원수평균점수문항매우 만족만족보통불만족매우 불만족
02023년59019278시스템 활용도101522577
12023년59019278업무의 투명성 및 효율성 향상611062410
22023년59019278시스템 제공 정보406571124
32023년59019278시스템 UI347466144
42023년59019278시스템 이용편의성337464138
52023년59019278시스템 운영자와 유선 연결64823682
62023년59019278시스템 운영자 태도66793773
72023년59019278민원처리시간59864241
82023년59019278민원처리결과62923521
92023년59019278시스템에 대한 전반적인 만족도41944575
년도전체대상수응답인원수평균점수문항매우 만족만족보통불만족매우 불만족
602017년52221083시스템 활용도127562232
612017년52221083시스템 사용으로 업무의 투명성 및 효율성 향상73129800
622017년52221083시스템 제공 정보4110157110
632017년52221083시스템 UI311125872
642017년52221083시스템 이용편의성411125070
652017년52221083시스템 운영자와 유선 연결681023262
662017년52221083시스템 운영자 태도109781931
672017년52221083민원처리시간86952513
682017년52221083민원처리결과89952312
692017년52221083시스템에 대한 전반적인 만족도541252650