Overview

Dataset statistics

Number of variables9
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory76.8 B

Variable types

Text4
Numeric1
Categorical4

Dataset

Description경상북도 문경시에서 민원 및 업무처리를 경험한 민원인(업체)을 대상으로 상시 민원만족도를 조사한 2021년 결과(연간 데이터)
Author경상북도 문경시
URLhttps://www.data.go.kr/data/15040107/fileData.do

Alerts

표본수 is highly overall correlated with 신속성 and 3 other fieldsHigh correlation
신속성 is highly overall correlated with 표본수 and 3 other fieldsHigh correlation
친절성 is highly overall correlated with 표본수 and 3 other fieldsHigh correlation
공정성 is highly overall correlated with 표본수 and 3 other fieldsHigh correlation
청렴성 is highly overall correlated with 표본수 and 3 other fieldsHigh correlation
부서명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:22:07.660215
Analysis finished2023-12-12 16:22:08.668171
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부서명칭
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T01:22:08.827280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.0571429
Min length3

Characters and Unicode

Total characters282
Distinct characters72
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row영순면
2nd row산양면
3rd row행정복지국>관광진흥과
4th row경제산업국>교통행정과
5th row경제산업국>농촌개발과
ValueCountFrequency (%)
영순면 1
 
2.9%
경제산업국>산림녹지과 1
 
2.9%
행정복지국>종합민원과 1
 
2.9%
가은읍 1
 
2.9%
호계면 1
 
2.9%
점촌5동 1
 
2.9%
경제산업국>일자리경제과 1
 
2.9%
농암면 1
 
2.9%
경제도시국>건축과 1
 
2.9%
점촌3동 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T01:22:09.205464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 21
 
7.4%
국 21
 
7.4%
> 21
 
7.4%
경 19
 
6.7%
제 16
 
5.7%
산 15
 
5.3%
업 13
 
4.6%
지 8
 
2.8%
도 8
 
2.8%
면 7
 
2.5%
Other values (62) 133
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 257
91.1%
Math Symbol 21
 
7.4%
Decimal Number 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 21
 
8.2%
국 21
 
8.2%
경 19
 
7.4%
제 16
 
6.2%
산 15
 
5.8%
업 13
 
5.1%
지 8
 
3.1%
도 8
 
3.1%
면 7
 
2.7%
시 7
 
2.7%
Other values (57) 122
47.5%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
3 1
25.0%
5 1
25.0%
4 1
25.0%
Math Symbol
ValueCountFrequency (%)
> 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 257
91.1%
Common 25
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 21
 
8.2%
국 21
 
8.2%
경 19
 
7.4%
제 16
 
6.2%
산 15
 
5.8%
업 13
 
5.1%
지 8
 
3.1%
도 8
 
3.1%
면 7
 
2.7%
시 7
 
2.7%
Other values (57) 122
47.5%
Common
ValueCountFrequency (%)
> 21
84.0%
2 1
 
4.0%
3 1
 
4.0%
5 1
 
4.0%
4 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 257
91.1%
ASCII 25
 
8.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 21
 
8.2%
국 21
 
8.2%
경 19
 
7.4%
제 16
 
6.2%
산 15
 
5.8%
업 13
 
5.1%
지 8
 
3.1%
도 8
 
3.1%
면 7
 
2.7%
시 7
 
2.7%
Other values (57) 122
47.5%
ASCII
ValueCountFrequency (%)
> 21
84.0%
2 1
 
4.0%
3 1
 
4.0%
5 1
 
4.0%
4 1
 
4.0%

표본수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1714286
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:22:09.356284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile24.1
Maximum31
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation8.0164746
Coefficient of variation (CV)1.1178351
Kurtosis2.3678717
Mean7.1714286
Median Absolute Deviation (MAD)3
Skewness1.7608452
Sum251
Variance64.263866
MonotonicityNot monotonic
2023-12-13T01:22:09.475450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 7
20.0%
3 7
20.0%
4 3
8.6%
2 3
8.6%
8 3
8.6%
7 2
 
5.7%
6 2
 
5.7%
29 1
 
2.9%
19 1
 
2.9%
14 1
 
2.9%
Other values (5) 5
14.3%
ValueCountFrequency (%)
1 7
20.0%
2 3
8.6%
3 7
20.0%
4 3
8.6%
5 1
 
2.9%
6 2
 
5.7%
7 2
 
5.7%
8 3
8.6%
14 1
 
2.9%
15 1
 
2.9%
ValueCountFrequency (%)
31 1
 
2.9%
29 1
 
2.9%
22 1
 
2.9%
20 1
 
2.9%
19 1
 
2.9%
15 1
 
2.9%
14 1
 
2.9%
8 3
8.6%
7 2
5.7%
6 2
5.7%

고객만족도
Text

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T01:22:09.651208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.2
Min length10

Characters and Unicode

Total characters357
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)60.0%

Sample

1st row100.0(4.7▲)
2nd row100.0(4.7▲)
3rd row100.0(4.7▲)
4th row100.0(4.7▲)
5th row100.0(4.7▲)
ValueCountFrequency (%)
100.0(4.7▲ 6
 
17.1%
96.7(1.4▲ 2
 
5.7%
95.0(0.3▼ 2
 
5.7%
99.3(4.0▲ 2
 
5.7%
93.5(1.8▼ 2
 
5.7%
94.3(1.0▼ 1
 
2.9%
95.5(0.2▲ 1
 
2.9%
88.5(6.8▼ 1
 
2.9%
90.5(4.8▼ 1
 
2.9%
91.0(4.3▼ 1
 
2.9%
Other values (16) 16
45.7%
2023-12-13T01:22:09.950981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 70
19.6%
0 39
10.9%
( 35
9.8%
) 35
9.8%
9 31
8.7%
▲ 22
 
6.2%
3 22
 
6.2%
1 19
 
5.3%
4 17
 
4.8%
7 16
 
4.5%
Other values (5) 51
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 182
51.0%
Other Punctuation 70
 
19.6%
Open Punctuation 35
 
9.8%
Close Punctuation 35
 
9.8%
Other Symbol 35
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39
21.4%
9 31
17.0%
3 22
12.1%
1 19
10.4%
4 17
9.3%
7 16
8.8%
8 13
 
7.1%
5 11
 
6.0%
6 8
 
4.4%
2 6
 
3.3%
Other Symbol
ValueCountFrequency (%)
▲ 22
62.9%
▼ 13
37.1%
Other Punctuation
ValueCountFrequency (%)
. 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 357
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 70
19.6%
0 39
10.9%
( 35
9.8%
) 35
9.8%
9 31
8.7%
▲ 22
 
6.2%
3 22
 
6.2%
1 19
 
5.3%
4 17
 
4.8%
7 16
 
4.5%
Other values (5) 51
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 322
90.2%
Geometric Shapes 35
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 70
21.7%
0 39
12.1%
( 35
10.9%
) 35
10.9%
9 31
9.6%
3 22
 
6.8%
1 19
 
5.9%
4 17
 
5.3%
7 16
 
5.0%
8 13
 
4.0%
Other values (3) 25
 
7.8%
Geometric Shapes
ValueCountFrequency (%)
▲ 22
62.9%
▼ 13
37.1%

신속성
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
100.0(4.8▲)
13 
90.0(5.2▼)
3 
95.0(0.2▼)
3 
97.5(2.3▲)
2 
95.5(0.3▲)
2 
Other values (11)
12 

Length

Max length11
Median length10
Mean length10.428571
Min length10

Unique

Unique10 ?
Unique (%)28.6%

Sample

1st row100.0(4.8▲)
2nd row100.0(4.8▲)
3rd row100.0(4.8▲)
4th row100.0(4.8▲)
5th row100.0(4.8▲)

Common Values

ValueCountFrequency (%)
100.0(4.8▲) 13
37.1%
90.0(5.2▼) 3
 
8.6%
95.0(0.2▼) 3
 
8.6%
97.5(2.3▲) 2
 
5.7%
95.5(0.3▲) 2
 
5.7%
80.0(15.2▼) 2
 
5.7%
97.9(2.7▲) 1
 
2.9%
96.7(1.5▲) 1
 
2.9%
97.1(1.9▲) 1
 
2.9%
93.3(1.9▼) 1
 
2.9%
Other values (6) 6
17.1%

Length

2023-12-13T01:22:10.072827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100.0(4.8▲ 13
37.1%
90.0(5.2▼ 3
 
8.6%
95.0(0.2▼ 3
 
8.6%
97.5(2.3▲ 2
 
5.7%
95.5(0.3▲ 2
 
5.7%
80.0(15.2▼ 2
 
5.7%
97.9(2.7▲ 1
 
2.9%
96.7(1.5▲ 1
 
2.9%
97.1(1.9▲ 1
 
2.9%
93.3(1.9▼ 1
 
2.9%
Other values (6) 6
17.1%

친절성
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
100.0(4.3▲)
13 
96.7(1.0▲)
4 
98.6(2.9▲)
2 
96.0(0.3▲)
2 
95.0(0.7▼)
2 
Other values (11)
12 

Length

Max length11
Median length10
Mean length10.428571
Min length10

Unique

Unique10 ?
Unique (%)28.6%

Sample

1st row100.0(4.3▲)
2nd row100.0(4.3▲)
3rd row100.0(4.3▲)
4th row100.0(4.3▲)
5th row100.0(4.3▲)

Common Values

ValueCountFrequency (%)
100.0(4.3▲) 13
37.1%
96.7(1.0▲) 4
 
11.4%
98.6(2.9▲) 2
 
5.7%
96.0(0.3▲) 2
 
5.7%
95.0(0.7▼) 2
 
5.7%
90.0(5.7▼) 2
 
5.7%
97.5(1.8▲) 1
 
2.9%
97.2(1.5▲) 1
 
2.9%
98.4(2.7▲) 1
 
2.9%
97.1(1.4▲) 1
 
2.9%
Other values (6) 6
17.1%

Length

2023-12-13T01:22:10.180529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100.0(4.3▲ 13
37.1%
96.7(1.0▲ 4
 
11.4%
98.6(2.9▲ 2
 
5.7%
96.0(0.3▲ 2
 
5.7%
95.0(0.7▼ 2
 
5.7%
90.0(5.7▼ 2
 
5.7%
97.5(1.8▲ 1
 
2.9%
97.2(1.5▲ 1
 
2.9%
98.4(2.7▲ 1
 
2.9%
97.1(1.4▲ 1
 
2.9%
Other values (6) 6
17.1%

전문성
Text

Distinct18
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T01:22:10.330928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.285714
Min length10

Characters and Unicode

Total characters360
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)34.3%

Sample

1st row100.0(5.8▲)
2nd row100.0(5.8▲)
3rd row100.0(5.8▲)
4th row100.0(5.8▲)
5th row100.0(5.8▲)
ValueCountFrequency (%)
100.0(5.8▲ 9
25.7%
90.0(4.2▼ 5
14.3%
96.7(2.5▲ 3
 
8.6%
97.5(3.3▲ 2
 
5.7%
94.7(0.5▲ 2
 
5.7%
92.5(1.7▼ 2
 
5.7%
95.8(1.6▲ 1
 
2.9%
95.0(0.8▲ 1
 
2.9%
86.7(7.5▼ 1
 
2.9%
88.8(5.4▼ 1
 
2.9%
Other values (8) 8
22.9%
2023-12-13T01:22:10.601925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 70
19.4%
0 45
12.5%
( 35
9.7%
) 35
9.7%
5 25
 
6.9%
9 23
 
6.4%
▲ 21
 
5.8%
8 20
 
5.6%
1 16
 
4.4%
2 15
 
4.2%
Other values (5) 55
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 185
51.4%
Other Punctuation 70
 
19.4%
Open Punctuation 35
 
9.7%
Close Punctuation 35
 
9.7%
Other Symbol 35
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
24.3%
5 25
13.5%
9 23
12.4%
8 20
10.8%
1 16
 
8.6%
2 15
 
8.1%
4 13
 
7.0%
7 13
 
7.0%
6 9
 
4.9%
3 6
 
3.2%
Other Symbol
ValueCountFrequency (%)
▲ 21
60.0%
▼ 14
40.0%
Other Punctuation
ValueCountFrequency (%)
. 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 70
19.4%
0 45
12.5%
( 35
9.7%
) 35
9.7%
5 25
 
6.9%
9 23
 
6.4%
▲ 21
 
5.8%
8 20
 
5.6%
1 16
 
4.4%
2 15
 
4.2%
Other values (5) 55
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 325
90.3%
Geometric Shapes 35
 
9.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 70
21.5%
0 45
13.8%
( 35
10.8%
) 35
10.8%
5 25
 
7.7%
9 23
 
7.1%
8 20
 
6.2%
1 16
 
4.9%
2 15
 
4.6%
4 13
 
4.0%
Other values (3) 28
 
8.6%
Geometric Shapes
ValueCountFrequency (%)
▲ 21
60.0%
▼ 14
40.0%

공정성
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
100.0(5.3▲)
13 
90.0(4.7▼)
4 
96.7(2.0▲)
3 
95.3(0.6▲)
2 
91.3(3.4▼)
2 
Other values (11)
11 

Length

Max length11
Median length10
Mean length10.4
Min length10

Unique

Unique11 ?
Unique (%)31.4%

Sample

1st row100.0(5.3▲)
2nd row100.0(5.3▲)
3rd row100.0(5.3▲)
4th row100.0(5.3▲)
5th row100.0(5.3▲)

Common Values

ValueCountFrequency (%)
100.0(5.3▲) 13
37.1%
90.0(4.7▼) 4
 
11.4%
96.7(2.0▲) 3
 
8.6%
95.3(0.6▲) 2
 
5.7%
91.3(3.4▼) 2
 
5.7%
97.5(2.8▲) 1
 
2.9%
96.9(2.2▲) 1
 
2.9%
95.7(1.0▲) 1
 
2.9%
93.3(1.4▼) 1
 
2.9%
94.5(0.2▼) 1
 
2.9%
Other values (6) 6
17.1%

Length

2023-12-13T01:22:10.718097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100.0(5.3▲ 13
37.1%
90.0(4.7▼ 4
 
11.4%
96.7(2.0▲ 3
 
8.6%
95.3(0.6▲ 2
 
5.7%
91.3(3.4▼ 2
 
5.7%
97.5(2.8▲ 1
 
2.9%
96.9(2.2▲ 1
 
2.9%
95.7(1.0▲ 1
 
2.9%
93.3(1.4▼ 1
 
2.9%
94.5(0.2▼ 1
 
2.9%
Other values (6) 6
17.1%

만족도
Text

Distinct18
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T01:22:10.843788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.4
Min length10

Characters and Unicode

Total characters364
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)40.0%

Sample

1st row100.0(5.6▲)
2nd row100.0(5.6▲)
3rd row100.0(5.6▲)
4th row100.0(5.6▲)
5th row100.0(5.6▲)
ValueCountFrequency (%)
100.0(5.6▲ 13
37.1%
96.7(2.3▲ 3
 
8.6%
90.0(4.4▼ 3
 
8.6%
95.0(0.6▲ 2
 
5.7%
92.5(1.9▼ 1
 
2.9%
93.3(1.1▼ 1
 
2.9%
85.0(9.4▼ 1
 
2.9%
88.8(5.6▼ 1
 
2.9%
90.5(3.9▼ 1
 
2.9%
92.0(2.4▼ 1
 
2.9%
Other values (8) 8
22.9%
2023-12-13T01:22:11.108501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 70
19.2%
0 56
15.4%
( 35
9.6%
) 35
9.6%
1 24
 
6.6%
▲ 23
 
6.3%
9 22
 
6.0%
5 21
 
5.8%
6 19
 
5.2%
4 13
 
3.6%
Other values (5) 46
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
51.9%
Other Punctuation 70
 
19.2%
Open Punctuation 35
 
9.6%
Close Punctuation 35
 
9.6%
Other Symbol 35
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 56
29.6%
1 24
12.7%
9 22
 
11.6%
5 21
 
11.1%
6 19
 
10.1%
4 13
 
6.9%
3 13
 
6.9%
7 8
 
4.2%
2 8
 
4.2%
8 5
 
2.6%
Other Symbol
ValueCountFrequency (%)
▲ 23
65.7%
▼ 12
34.3%
Other Punctuation
ValueCountFrequency (%)
. 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 70
19.2%
0 56
15.4%
( 35
9.6%
) 35
9.6%
1 24
 
6.6%
▲ 23
 
6.3%
9 22
 
6.0%
5 21
 
5.8%
6 19
 
5.2%
4 13
 
3.6%
Other values (5) 46
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
90.4%
Geometric Shapes 35
 
9.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 70
21.3%
0 56
17.0%
( 35
10.6%
) 35
10.6%
1 24
 
7.3%
9 22
 
6.7%
5 21
 
6.4%
6 19
 
5.8%
4 13
 
4.0%
3 13
 
4.0%
Other values (3) 21
 
6.4%
Geometric Shapes
ValueCountFrequency (%)
▲ 23
65.7%
▼ 12
34.3%

청렴성
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
100.0(2.4▲)
18 
96.7(0.9▼)
2 
95.0(2.6▼)
2 
97.5(0.1▼)
2 
99.3(1.7▲)
 
1
Other values (10)
10 

Length

Max length11
Median length11
Mean length10.514286
Min length10

Unique

Unique11 ?
Unique (%)31.4%

Sample

1st row100.0(2.4▲)
2nd row100.0(2.4▲)
3rd row100.0(2.4▲)
4th row100.0(2.4▲)
5th row100.0(2.4▲)

Common Values

ValueCountFrequency (%)
100.0(2.4▲) 18
51.4%
96.7(0.9▼) 2
 
5.7%
95.0(2.6▼) 2
 
5.7%
97.5(0.1▼) 2
 
5.7%
99.3(1.7▲) 1
 
2.9%
96.8(0.8▼) 1
 
2.9%
97.1(0.5▼) 1
 
2.9%
97.3(0.3▼) 1
 
2.9%
96.5(1.1▼) 1
 
2.9%
98.3(0.7▲) 1
 
2.9%
Other values (5) 5
 
14.3%

Length

2023-12-13T01:22:11.236158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100.0(2.4▲ 18
51.4%
96.7(0.9▼ 2
 
5.7%
95.0(2.6▼ 2
 
5.7%
97.5(0.1▼ 2
 
5.7%
99.3(1.7▲ 1
 
2.9%
96.8(0.8▼ 1
 
2.9%
97.1(0.5▼ 1
 
2.9%
97.3(0.3▼ 1
 
2.9%
96.5(1.1▼ 1
 
2.9%
98.3(0.7▲ 1
 
2.9%
Other values (5) 5
 
14.3%

Interactions

2023-12-13T01:22:08.084570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:22:11.325439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명칭표본수고객만족도신속성친절성전문성공정성만족도청렴성
부서명칭1.0001.0001.0001.0001.0001.0001.0001.0001.000
표본수1.0001.0000.9380.8900.9070.9440.9100.9630.937
고객만족도1.0000.9381.0000.9600.9630.9790.9790.9790.964
신속성1.0000.8900.9601.0000.9710.9280.9640.9620.941
친절성1.0000.9070.9630.9711.0000.9510.9630.9830.954
전문성1.0000.9440.9790.9280.9511.0000.9440.9890.943
공정성1.0000.9100.9790.9640.9630.9441.0000.9540.962
만족도1.0000.9630.9790.9620.9830.9890.9541.0000.984
청렴성1.0000.9370.9640.9410.9540.9430.9620.9841.000
2023-12-13T01:22:11.432384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
친절성신속성공정성청렴성
친절성1.0000.6280.5890.709
신속성0.6281.0000.5970.666
공정성0.5890.5971.0000.742
청렴성0.7090.6660.7421.000
2023-12-13T01:22:11.521857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표본수신속성친절성공정성청렴성
표본수1.0000.6680.6750.5920.737
신속성0.6681.0000.6280.5970.666
친절성0.6750.6281.0000.5890.709
공정성0.5920.5970.5891.0000.742
청렴성0.7370.6660.7090.7421.000

Missing values

2023-12-13T01:22:08.470397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:22:08.617173image/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

부서명칭표본수고객만족도신속성친절성전문성공정성만족도청렴성
0영순면1100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
1산양면4100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
2행정복지국>관광진흥과1100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
3경제산업국>교통행정과2100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
4경제산업국>농촌개발과1100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
5문화관광농업국>농촌활력과1100.0(4.7▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
6산북면799.7(4.4▲)100.0(4.8▲)98.6(2.9▲)100.0(5.8▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
7문경읍399.3(4.0▲)100.0(4.8▲)100.0(4.3▲)96.7(2.5▲)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
8문화관광농업국>유통축산과399.3(4.0▲)100.0(4.8▲)100.0(4.3▲)100.0(5.8▲)96.7(2.0▲)100.0(5.6▲)100.0(2.4▲)
9점촌4동399.0(3.7▲)100.0(4.8▲)100.0(4.3▲)93.3(0.9▼)100.0(5.3▲)100.0(5.6▲)100.0(2.4▲)
부서명칭표본수고객만족도신속성친절성전문성공정성만족도청렴성
25농암면694.2(1.1▼)95.0(0.2▼)96.7(1.0▲)90.0(4.2▼)91.7(3.0▼)93.3(1.1▼)98.3(0.7▲)
26점촌3동293.5(1.8▼)95.0(0.2▼)95.0(0.7▼)95.0(0.8▲)90.0(4.7▼)90.0(4.4▼)95.0(2.6▼)
27경제산업국>유통축산과893.5(1.8▼)96.3(1.1▲)92.5(3.2▼)92.5(1.7▼)91.3(3.4▼)91.3(3.1▼)96.3(1.3▼)
28동로면193.0(2.3▼)80.0(15.2▼)100.0(4.3▲)90.0(4.2▼)100.0(5.3▲)90.0(4.4▼)100.0(2.4▲)
29점촌2동592.0(3.3▼)96.0(0.8▲)94.0(1.7▼)88.0(6.2▼)86.0(8.7▼)92.0(2.4▼)96.0(1.6▼)
30경제산업국>도시과2291.7(3.6▼)90.0(5.2▼)90.0(5.7▼)91.4(2.8▼)91.8(2.9▼)90.5(3.9▼)96.4(1.2▼)
31경제도시국>도시과891.0(4.3▼)91.3(3.9▼)90.0(5.7▼)88.8(5.4▼)90.0(4.7▼)88.8(5.6▼)97.5(0.1▼)
32상수도사업소290.5(4.8▼)95.0(0.2▼)95.0(0.7▼)90.0(4.2▼)85.0(9.7▼)90.0(4.4▼)90.0(7.6▼)
33경제도시국>일자리경제과688.5(6.8▼)86.7(8.5▼)85.0(10.7▼)86.7(7.5▼)90.0(4.7▼)85.0(9.4▼)96.7(0.9▼)
34경제산업국>건설과382.3(13.0▼)80.0(15.2▼)83.3(12.4▼)80.0(14.2▼)83.3(11.4▼)73.3(21.1▼)93.3(4.3▼)