Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory84.1 B

Variable types

Categorical1
Text1
Numeric7

Dataset

Description울산시설공단 고객만족도 조사 결과 데이터로서 연도, 시설, 응답자수, 종합만족도, 서비스환경, 서비스과정 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15087227/fileData.do

Alerts

종합 만족도 is highly overall correlated with 서비스환경 만족도 and 4 other fieldsHigh correlation
서비스환경 만족도 is highly overall correlated with 종합 만족도 and 4 other fieldsHigh correlation
서비스과정 만족도 is highly overall correlated with 종합 만족도 and 4 other fieldsHigh correlation
서비스결과 만족도 is highly overall correlated with 종합 만족도 and 4 other fieldsHigh correlation
사회적 만족도 is highly overall correlated with 종합 만족도 and 4 other fieldsHigh correlation
전반적 만족도 is highly overall correlated with 종합 만족도 and 4 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 12:23:52.830671
Analysis finished2023-12-12 12:23:59.249549
Duration6.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
2022
13 
2021
12 
2020
7 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2022 13
40.6%
2021 12
37.5%
2020 7
21.9%

Length

2023-12-12T21:23:59.314201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:23:59.434467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 13
40.6%
2021 12
37.5%
2020 7
21.9%

시설
Text

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T21:23:59.636859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.53125
Min length5

Characters and Unicode

Total characters209
Distinct characters52
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)15.6%

Sample

1st row울산시설공단
2nd row울산대공원 수영장
3rd row문수체육시설
4th row동천국민체육센터
5th row가족문화센터
ValueCountFrequency (%)
울산시설공단 3
9.1%
문수체육시설 3
9.1%
동천국민체육센터 3
9.1%
가족문화센터 3
9.1%
여성인력개발센터 3
9.1%
울산대공원 3
9.1%
울산대공원수영장 2
 
6.1%
노동복지관 2
 
6.1%
어린이테마파크 2
 
6.1%
울산체육공원 2
 
6.1%
Other values (6) 7
21.2%
2023-12-12T21:24:00.006915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
울 12
 
5.7%
산 12
 
5.7%
공 12
 
5.7%
체 9
 
4.3%
터 9
 
4.3%
센 9
 
4.3%
육 9
 
4.3%
원 9
 
4.3%
수 7
 
3.3%
동 7
 
3.3%
Other values (42) 114
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
99.5%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
울 12
 
5.8%
산 12
 
5.8%
공 12
 
5.8%
체 9
 
4.3%
터 9
 
4.3%
센 9
 
4.3%
육 9
 
4.3%
원 9
 
4.3%
수 7
 
3.4%
동 7
 
3.4%
Other values (41) 113
54.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
울 12
 
5.8%
산 12
 
5.8%
공 12
 
5.8%
체 9
 
4.3%
터 9
 
4.3%
센 9
 
4.3%
육 9
 
4.3%
원 9
 
4.3%
수 7
 
3.4%
동 7
 
3.4%
Other values (41) 113
54.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
99.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
울 12
 
5.8%
산 12
 
5.8%
공 12
 
5.8%
체 9
 
4.3%
터 9
 
4.3%
센 9
 
4.3%
육 9
 
4.3%
원 9
 
4.3%
수 7
 
3.4%
동 7
 
3.4%
Other values (41) 113
54.3%
ASCII
ValueCountFrequency (%)
1
100.0%

응답자수(명)
Real number (ℝ)

Distinct12
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.5
Minimum25
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:00.214300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile25
Q138.75
median50
Q392.5
95-th percentile600
Maximum600
Range575
Interquartile range (IQR)53.75

Descriptive statistics

Standard deviation163.44576
Coefficient of variation (CV)1.4528512
Kurtosis6.0179913
Mean112.5
Median Absolute Deviation (MAD)22.5
Skewness2.6759486
Sum3600
Variance26714.516
MonotonicityNot monotonic
2023-12-12T21:24:00.329059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
50 5
15.6%
25 5
15.6%
40 4
12.5%
600 3
9.4%
90 3
9.4%
60 3
9.4%
140 2
 
6.2%
100 2
 
6.2%
30 2
 
6.2%
170 1
 
3.1%
Other values (2) 2
 
6.2%
ValueCountFrequency (%)
25 5
15.6%
30 2
 
6.2%
35 1
 
3.1%
40 4
12.5%
50 5
15.6%
60 3
9.4%
70 1
 
3.1%
90 3
9.4%
100 2
 
6.2%
140 2
 
6.2%
ValueCountFrequency (%)
600 3
9.4%
170 1
 
3.1%
140 2
 
6.2%
100 2
 
6.2%
90 3
9.4%
70 1
 
3.1%
60 3
9.4%
50 5
15.6%
40 4
12.5%
35 1
 
3.1%

종합 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.6625
Minimum74.9
Maximum92.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:00.467447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74.9
5-th percentile78.46
Q183.675
median86.6
Q388.75
95-th percentile90.3
Maximum92.8
Range17.9
Interquartile range (IQR)5.075

Descriptive statistics

Standard deviation4.0215348
Coefficient of variation (CV)0.046946269
Kurtosis0.54585507
Mean85.6625
Median Absolute Deviation (MAD)2.5
Skewness-0.80614614
Sum2741.2
Variance16.172742
MonotonicityNot monotonic
2023-12-12T21:24:00.623065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
90.3 2
 
6.2%
89.1 2
 
6.2%
86.5 1
 
3.1%
88.9 1
 
3.1%
85.1 1
 
3.1%
90.1 1
 
3.1%
82.4 1
 
3.1%
81.1 1
 
3.1%
83.8 1
 
3.1%
85.6 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
74.9 1
3.1%
77.8 1
3.1%
79.0 1
3.1%
79.7 1
3.1%
81.1 1
3.1%
82.4 1
3.1%
83.3 1
3.1%
83.6 1
3.1%
83.7 1
3.1%
83.8 1
3.1%
ValueCountFrequency (%)
92.8 1
3.1%
90.3 2
6.2%
90.1 1
3.1%
89.6 1
3.1%
89.1 2
6.2%
88.9 1
3.1%
88.7 1
3.1%
87.9 1
3.1%
87.6 1
3.1%
87.3 1
3.1%

서비스환경 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.95625
Minimum74.8
Maximum92.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:01.138958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74.8
5-th percentile78.665
Q185.025
median86.95
Q388
95-th percentile90.6
Maximum92.2
Range17.4
Interquartile range (IQR)2.975

Descriptive statistics

Standard deviation3.9797826
Coefficient of variation (CV)0.046300095
Kurtosis1.0510354
Mean85.95625
Median Absolute Deviation (MAD)1.5
Skewness-1.1122159
Sum2750.6
Variance15.838669
MonotonicityNot monotonic
2023-12-12T21:24:01.307394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
82.8 2
 
6.2%
90.6 2
 
6.2%
87.0 2
 
6.2%
78.8 2
 
6.2%
87.1 2
 
6.2%
88.0 2
 
6.2%
84.2 1
 
3.1%
86.9 1
 
3.1%
89.4 1
 
3.1%
81.0 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
74.8 1
3.1%
78.5 1
3.1%
78.8 2
6.2%
81.0 1
3.1%
82.8 2
6.2%
84.2 1
3.1%
85.3 1
3.1%
85.6 1
3.1%
85.8 1
3.1%
86.5 1
3.1%
ValueCountFrequency (%)
92.2 1
3.1%
90.6 2
6.2%
90.5 1
3.1%
89.6 1
3.1%
89.4 1
3.1%
88.8 1
3.1%
88.0 2
6.2%
87.9 1
3.1%
87.7 1
3.1%
87.2 1
3.1%

서비스과정 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.475
Minimum75.1
Maximum91.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:01.485848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75.1
5-th percentile78.535
Q183.7
median86.4
Q388.075
95-th percentile89.99
Maximum91.9
Range16.8
Interquartile range (IQR)4.375

Descriptive statistics

Standard deviation3.7954982
Coefficient of variation (CV)0.044404775
Kurtosis0.69555918
Mean85.475
Median Absolute Deviation (MAD)2.45
Skewness-0.85190553
Sum2735.2
Variance14.405806
MonotonicityNot monotonic
2023-12-12T21:24:01.626896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
83.9 2
 
6.2%
88.7 2
 
6.2%
86.5 1
 
3.1%
83.8 1
 
3.1%
82.5 1
 
3.1%
82.2 1
 
3.1%
84.9 1
 
3.1%
86.8 1
 
3.1%
75.1 1
 
3.1%
87.3 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
75.1 1
3.1%
77.6 1
3.1%
79.3 1
3.1%
80.5 1
3.1%
82.2 1
3.1%
82.5 1
3.1%
82.6 1
3.1%
83.4 1
3.1%
83.8 1
3.1%
83.9 2
6.2%
ValueCountFrequency (%)
91.9 1
3.1%
90.1 1
3.1%
89.9 1
3.1%
89.8 1
3.1%
89.0 1
3.1%
88.7 2
6.2%
88.3 1
3.1%
88.0 1
3.1%
87.7 1
3.1%
87.5 1
3.1%

서비스결과 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.16875
Minimum74.8
Maximum92.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:01.773160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74.8
5-th percentile78.68
Q183
median86
Q387.675
95-th percentile89.845
Maximum92.1
Range17.3
Interquartile range (IQR)4.675

Descriptive statistics

Standard deviation3.8662675
Coefficient of variation (CV)0.045395377
Kurtosis0.46296816
Mean85.16875
Median Absolute Deviation (MAD)2.25
Skewness-0.73922859
Sum2725.4
Variance14.948024
MonotonicityNot monotonic
2023-12-12T21:24:01.909680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
86.7 3
 
9.4%
86.0 2
 
6.2%
88.9 1
 
3.1%
84.0 1
 
3.1%
89.8 1
 
3.1%
81.6 1
 
3.1%
80.5 1
 
3.1%
84.1 1
 
3.1%
83.9 1
 
3.1%
74.8 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
74.8 1
3.1%
77.8 1
3.1%
79.4 1
3.1%
79.7 1
3.1%
80.5 1
3.1%
81.6 1
3.1%
82.4 1
3.1%
82.7 1
3.1%
83.1 1
3.1%
83.9 1
3.1%
ValueCountFrequency (%)
92.1 1
3.1%
89.9 1
3.1%
89.8 1
3.1%
89.5 1
3.1%
89.0 1
3.1%
88.9 1
3.1%
88.3 1
3.1%
88.2 1
3.1%
87.5 1
3.1%
87.2 1
3.1%

사회적 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.515625
Minimum58.1
Maximum93.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:02.047518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58.1
5-th percentile77.8
Q183.6
median87.35
Q389.325
95-th percentile90.88
Maximum93.9
Range35.8
Interquartile range (IQR)5.725

Descriptive statistics

Standard deviation6.4519119
Coefficient of variation (CV)0.07544717
Kurtosis9.8929586
Mean85.515625
Median Absolute Deviation (MAD)3.1
Skewness-2.6103548
Sum2736.5
Variance41.627167
MonotonicityNot monotonic
2023-12-12T21:24:02.183131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
90.7 3
 
9.4%
88.6 2
 
6.2%
87.2 2
 
6.2%
77.8 2
 
6.2%
88.3 2
 
6.2%
83.9 2
 
6.2%
87.7 1
 
3.1%
89.3 1
 
3.1%
85.2 1
 
3.1%
81.8 1
 
3.1%
Other values (15) 15
46.9%
ValueCountFrequency (%)
58.1 1
3.1%
77.8 2
6.2%
79.2 1
3.1%
80.8 1
3.1%
81.6 1
3.1%
81.8 1
3.1%
82.7 1
3.1%
83.9 2
6.2%
84.3 1
3.1%
84.9 1
3.1%
ValueCountFrequency (%)
93.9 1
 
3.1%
91.1 1
 
3.1%
90.7 3
9.4%
90.5 1
 
3.1%
89.5 1
 
3.1%
89.4 1
 
3.1%
89.3 1
 
3.1%
88.9 1
 
3.1%
88.6 2
6.2%
88.3 2
6.2%

전반적 만족도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.54375
Minimum72.9
Maximum93.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T21:24:02.324260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum72.9
5-th percentile77.975
Q183.25
median86.4
Q388.95
95-th percentile90.77
Maximum93.5
Range20.6
Interquartile range (IQR)5.7

Descriptive statistics

Standard deviation4.4663572
Coefficient of variation (CV)0.05221138
Kurtosis0.88441209
Mean85.54375
Median Absolute Deviation (MAD)2.75
Skewness-0.86230609
Sum2737.4
Variance19.948347
MonotonicityNot monotonic
2023-12-12T21:24:02.491122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
89.1 2
 
6.2%
87.1 2
 
6.2%
86.4 2
 
6.2%
86.2 1
 
3.1%
86.8 1
 
3.1%
85.9 1
 
3.1%
91.1 1
 
3.1%
83.1 1
 
3.1%
81.0 1
 
3.1%
82.8 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
72.9 1
3.1%
77.7 1
3.1%
78.2 1
3.1%
78.4 1
3.1%
81.0 1
3.1%
82.6 1
3.1%
82.8 1
3.1%
83.1 1
3.1%
83.3 1
3.1%
83.6 1
3.1%
ValueCountFrequency (%)
93.5 1
3.1%
91.1 1
3.1%
90.5 1
3.1%
90.3 1
3.1%
89.8 1
3.1%
89.3 1
3.1%
89.1 2
6.2%
88.9 1
3.1%
88.2 1
3.1%
88.1 1
3.1%

Interactions

2023-12-12T21:23:58.397424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.161458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.265909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.080422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.934868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.804908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.657926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.484146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.251005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.376578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.182528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.056749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.939627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.764684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.570096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.375590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.492699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.313315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.186277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.074369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.889784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.663667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.489185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.603596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.420003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.305859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.196959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.012592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.747015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.957597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.728721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.570254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.430277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.304144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.124301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.834482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.064895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.850862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.692828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.556233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.433597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.215491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.926888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.166125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:54.976477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:55.832501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:56.689523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:57.561571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:58.315517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:24:02.628857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시설응답자수(명)종합 만족도서비스환경 만족도서비스과정 만족도서비스결과 만족도사회적 만족도전반적 만족도
연도1.0000.0000.1690.0000.0000.0000.0000.3880.000
시설0.0001.0000.7750.6490.0000.7140.6760.6740.378
응답자수(명)0.1690.7751.0000.0540.0000.0000.1210.0000.417
종합 만족도0.0000.6490.0541.0000.8690.9840.9880.8250.964
서비스환경 만족도0.0000.0000.0000.8691.0000.7740.8150.7550.947
서비스과정 만족도0.0000.7140.0000.9840.7741.0000.9800.8240.890
서비스결과 만족도0.0000.6760.1210.9880.8150.9801.0000.8240.926
사회적 만족도0.3880.6740.0000.8250.7550.8240.8241.0000.843
전반적 만족도0.0000.3780.4170.9640.9470.8900.9260.8431.000
2023-12-12T21:24:02.785632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
응답자수(명)종합 만족도서비스환경 만족도서비스과정 만족도서비스결과 만족도사회적 만족도전반적 만족도연도
응답자수(명)1.000-0.0540.008-0.097-0.035-0.057-0.0280.147
종합 만족도-0.0541.0000.9310.9800.9800.9580.9880.000
서비스환경 만족도0.0080.9311.0000.9090.8990.8770.9060.000
서비스과정 만족도-0.0970.9800.9091.0000.9470.9330.9600.000
서비스결과 만족도-0.0350.9800.8990.9471.0000.9410.9770.000
사회적 만족도-0.0570.9580.8770.9330.9411.0000.9440.149
전반적 만족도-0.0280.9880.9060.9600.9770.9441.0000.000
연도0.1470.0000.0000.0000.0000.1490.0001.000

Missing values

2023-12-12T21:23:59.032974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:23:59.185754image/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

연도시설응답자수(명)종합 만족도서비스환경 만족도서비스과정 만족도서비스결과 만족도사회적 만족도전반적 만족도
02020울산시설공단60086.586.586.586.087.786.2
12020울산대공원 수영장14092.892.291.992.193.993.5
22020문수체육시설17090.390.689.889.591.190.5
32020동천국민체육센터9087.688.887.486.988.687.2
42020가족문화센터5088.787.988.088.289.489.1
52020근로자종합복지회관5084.187.084.582.758.183.3
62020여성인력개발센터10079.778.880.579.781.678.2
72021울산시설공단60087.187.186.986.787.587.1
82021동천체육관14086.487.186.385.587.286.4
92021동천국민체육센터4083.386.884.082.482.782.6
연도시설응답자수(명)종합 만족도서비스환경 만족도서비스과정 만족도서비스결과 만족도사회적 만족도전반적 만족도
222022울산대공원수영장10079.078.879.379.479.278.4
232022문수체육시설2586.985.387.386.488.686.4
242022동천국민체육센터2574.974.875.174.877.872.9
252022가족문화센터2587.387.286.886.788.987.1
262022노동복지관5085.687.084.983.988.384.8
272022어린이테마파크5083.885.883.984.183.982.8
282022여성인력개발센터7081.181.082.280.580.881.0
292022울산대공원6082.482.882.581.681.883.1
302022울산체육공원3090.189.488.789.890.791.1
312022울산하늘공원9085.186.983.984.085.285.9