Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory57.9 B

Variable types

Text1
Numeric5

Dataset

Description기관에서 구매한 친환경 제품에 대한 정보(구분, 총구매금액, 녹색구매금액, 구매율)
Author한국전력공사
URLhttps://www.data.go.kr/data/15017200/fileData.do

Alerts

총구매금액(A)(천원) is highly overall correlated with 제외승인(B)(천원) and 2 other fieldsHigh correlation
제외승인(B)(천원) is highly overall correlated with 총구매금액(A)(천원)High correlation
제외후금액(A-B)(천원) is highly overall correlated with 총구매금액(A)(천원) and 1 other fieldsHigh correlation
녹색구매금액(C)(천원) is highly overall correlated with 총구매금액(A)(천원) and 1 other fieldsHigh correlation
구분 has unique valuesUnique
총구매금액(A)(천원) has unique valuesUnique
제외후금액(A-B)(천원) has unique valuesUnique
녹색구매금액(C)(천원) has unique valuesUnique
제외승인(B)(천원) has 21 (77.8%) zerosZeros

Reproduction

Analysis started2023-12-12 05:05:15.077125
Analysis finished2023-12-12 05:05:18.603557
Duration3.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T14:05:18.743893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length13.074074
Min length6

Characters and Unicode

Total characters353
Distinct characters58
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row한국전력공사
2nd row한국전력공사 대구지역본부
3rd row한국전력공사 경남지역본부
4th row한국전력공사 강원지역본부
5th row한국전력공사 전북지역본부
ValueCountFrequency (%)
한국전력공사 27
50.9%
전력연구원 1
 
1.9%
충북지역본부 1
 
1.9%
대전충남지역본부 1
 
1.9%
업무지원처 1
 
1.9%
경북지역본부 1
 
1.9%
제주지역본부 1
 
1.9%
수안보생활연수원 1
 
1.9%
전력기반조성사업센터 1
 
1.9%
ict인프라처 1
 
1.9%
Other values (17) 17
32.1%
2023-12-12T14:05:19.123788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 32
 
9.1%
력 29
 
8.2%
사 28
 
7.9%
한 27
 
7.6%
공 27
 
7.6%
국 27
 
7.6%
26
 
7.4%
부 20
 
5.7%
본 16
 
4.5%
지 16
 
4.5%
Other values (48) 105
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
91.8%
Space Separator 26
 
7.4%
Uppercase Letter 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 32
 
9.9%
력 29
 
9.0%
사 28
 
8.6%
한 27
 
8.3%
공 27
 
8.3%
국 27
 
8.3%
부 20
 
6.2%
본 16
 
4.9%
지 16
 
4.9%
역 15
 
4.6%
Other values (44) 87
26.9%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
T 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
91.8%
Common 26
 
7.4%
Latin 3
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 32
 
9.9%
력 29
 
9.0%
사 28
 
8.6%
한 27
 
8.3%
공 27
 
8.3%
국 27
 
8.3%
부 20
 
6.2%
본 16
 
4.9%
지 16
 
4.9%
역 15
 
4.6%
Other values (44) 87
26.9%
Latin
ValueCountFrequency (%)
I 1
33.3%
T 1
33.3%
C 1
33.3%
Common
ValueCountFrequency (%)
26
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
91.8%
ASCII 29
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 32
 
9.9%
력 29
 
9.0%
사 28
 
8.6%
한 27
 
8.3%
공 27
 
8.3%
국 27
 
8.3%
부 20
 
6.2%
본 16
 
4.9%
지 16
 
4.9%
역 15
 
4.6%
Other values (44) 87
26.9%
ASCII
ValueCountFrequency (%)
26
89.7%
I 1
 
3.4%
T 1
 
3.4%
C 1
 
3.4%

총구매금액(A)(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1221524.7
Minimum9970
Maximum3697186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T14:05:19.286056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9970
5-th percentile21851.7
Q1463699
median851741
Q31625080
95-th percentile3204913.4
Maximum3697186
Range3687216
Interquartile range (IQR)1161381

Descriptive statistics

Standard deviation1103466.8
Coefficient of variation (CV)0.90335202
Kurtosis-0.33434933
Mean1221524.7
Median Absolute Deviation (MAD)695635
Skewness0.86630791
Sum32981166
Variance1.2176389 × 1012
MonotonicityNot monotonic
2023-12-12T14:05:19.471497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1401872 1
 
3.7%
1136534 1
 
3.7%
851741 1
 
3.7%
683972 1
 
3.7%
3697186 1
 
3.7%
514592 1
 
3.7%
746388 1
 
3.7%
2516153 1
 
3.7%
43576 1
 
3.7%
13530 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
9970 1
3.7%
13530 1
3.7%
41269 1
3.7%
43576 1
3.7%
74584 1
3.7%
148914 1
3.7%
412806 1
3.7%
514592 1
3.7%
533982 1
3.7%
629786 1
3.7%
ValueCountFrequency (%)
3697186 1
3.7%
3321569 1
3.7%
2932717 1
3.7%
2906906 1
3.7%
2649708 1
3.7%
2516153 1
3.7%
1702784 1
3.7%
1547376 1
3.7%
1527469 1
3.7%
1401872 1
3.7%

제외승인(B)(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207639.63
Minimum0
Maximum2593495
Zeros21
Zeros (%)77.8%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T14:05:19.622946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1107222.6
Maximum2593495
Range2593495
Interquartile range (IQR)0

Descriptive statistics

Standard deviation562611.73
Coefficient of variation (CV)2.7095585
Kurtosis12.9876
Mean207639.63
Median Absolute Deviation (MAD)0
Skewness3.4518493
Sum5606270
Variance3.1653196 × 1011
MonotonicityNot monotonic
2023-12-12T14:05:19.750796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 21
77.8%
1277892 1
 
3.7%
2593495 1
 
3.7%
570049 1
 
3.7%
708994 1
 
3.7%
800 1
 
3.7%
455040 1
 
3.7%
ValueCountFrequency (%)
0 21
77.8%
800 1
 
3.7%
455040 1
 
3.7%
570049 1
 
3.7%
708994 1
 
3.7%
1277892 1
 
3.7%
2593495 1
 
3.7%
ValueCountFrequency (%)
2593495 1
 
3.7%
1277892 1
 
3.7%
708994 1
 
3.7%
570049 1
 
3.7%
455040 1
 
3.7%
800 1
 
3.7%
0 21
77.8%

제외후금액(A-B)(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1013885.1
Minimum9970
Maximum3697186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T14:05:19.875005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9970
5-th percentile21851.7
Q1231163
median683972
Q31204470.5
95-th percentile3204673.4
Maximum3697186
Range3687216
Interquartile range (IQR)973307.5

Descriptive statistics

Standard deviation1047377.6
Coefficient of variation (CV)1.0330338
Kurtosis0.98893761
Mean1013885.1
Median Absolute Deviation (MAD)535058
Skewness1.3512094
Sum27374897
Variance1.0969998 × 1012
MonotonicityNot monotonic
2023-12-12T14:05:20.031173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
123980 1
 
3.7%
1136534 1
 
3.7%
851741 1
 
3.7%
683972 1
 
3.7%
3697186 1
 
3.7%
514592 1
 
3.7%
746388 1
 
3.7%
2061113 1
 
3.7%
43576 1
 
3.7%
13530 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
9970 1
3.7%
13530 1
3.7%
41269 1
3.7%
43576 1
3.7%
74584 1
3.7%
123980 1
3.7%
148914 1
3.7%
313412 1
3.7%
412806 1
3.7%
514592 1
3.7%
ValueCountFrequency (%)
3697186 1
3.7%
3321569 1
3.7%
2931917 1
3.7%
2649708 1
3.7%
2061113 1
3.7%
1547376 1
3.7%
1272407 1
3.7%
1136534 1
3.7%
1132735 1
3.7%
998475 1
3.7%

녹색구매금액(C)(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean971030
Minimum880
Maximum3637101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T14:05:20.201962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum880
5-th percentile11149.6
Q1191862
median666373
Q31094055
95-th percentile3104793
Maximum3637101
Range3636221
Interquartile range (IQR)902193

Descriptive statistics

Standard deviation1032954.1
Coefficient of variation (CV)1.0637716
Kurtosis1.0018941
Mean971030
Median Absolute Deviation (MAD)450648
Skewness1.3621091
Sum26217810
Variance1.0669943 × 1012
MonotonicityNot monotonic
2023-12-12T14:05:20.379415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
114164 1
 
3.7%
1117021 1
 
3.7%
814474 1
 
3.7%
666373 1
 
3.7%
3637101 1
 
3.7%
442798 1
 
3.7%
713413 1
 
3.7%
2061113 1
 
3.7%
36494 1
 
3.7%
880 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
880 1
3.7%
9970 1
3.7%
13902 1
3.7%
36494 1
3.7%
41269 1
3.7%
114164 1
3.7%
132284 1
3.7%
251440 1
3.7%
294235 1
3.7%
442798 1
3.7%
ValueCountFrequency (%)
3637101 1
3.7%
3249126 1
3.7%
2768016 1
3.7%
2640610 1
3.7%
2061113 1
3.7%
1547376 1
3.7%
1117021 1
3.7%
1071089 1
3.7%
1036530 1
3.7%
983531 1
3.7%

구매율[C/(A-B)*100]
Real number (ℝ)

Distinct22
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.685185
Minimum6.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T14:05:20.529699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.5
5-th percentile34.41
Q187.4
median95.6
Q398.7
95-th percentile100
Maximum100
Range93.5
Interquartile range (IQR)11.3

Descriptive statistics

Standard deviation22.926718
Coefficient of variation (CV)0.26146626
Kurtosis8.2893221
Mean87.685185
Median Absolute Deviation (MAD)4.1
Skewness-2.9268752
Sum2367.5
Variance525.63439
MonotonicityNot monotonic
2023-12-12T14:05:20.669418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
100.0 5
18.5%
95.6 2
 
7.4%
92.1 1
 
3.7%
97.8 1
 
3.7%
97.4 1
 
3.7%
98.4 1
 
3.7%
86.0 1
 
3.7%
83.7 1
 
3.7%
6.5 1
 
3.7%
99.7 1
 
3.7%
Other values (12) 12
44.4%
ValueCountFrequency (%)
6.5 1
3.7%
18.6 1
3.7%
71.3 1
3.7%
80.2 1
3.7%
81.5 1
3.7%
83.7 1
3.7%
86.0 1
3.7%
88.8 1
3.7%
92.1 1
3.7%
92.4 1
3.7%
ValueCountFrequency (%)
100.0 5
18.5%
99.7 1
 
3.7%
98.9 1
 
3.7%
98.5 1
 
3.7%
98.4 1
 
3.7%
98.3 1
 
3.7%
97.8 1
 
3.7%
97.4 1
 
3.7%
97.2 1
 
3.7%
95.6 2
 
7.4%

Interactions

2023-12-12T14:05:17.852809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.307315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.871042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.415022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.321417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.961838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.417406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.985566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.514489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.428271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:18.075943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.525639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.071500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.609587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.532342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:18.197441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.643318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.169060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.718071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.649615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:18.298523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:15.749491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:16.294357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.222883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:05:17.757350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:05:20.770765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분총구매금액(A)(천원)제외승인(B)(천원)제외후금액(A-B)(천원)녹색구매금액(C)(천원)구매율[C/(A-B)*100]
구분1.0001.0001.0001.0001.0001.000
총구매금액(A)(천원)1.0001.0000.7840.9880.9780.000
제외승인(B)(천원)1.0000.7841.0000.4830.5080.439
제외후금액(A-B)(천원)1.0000.9880.4831.0000.9960.000
녹색구매금액(C)(천원)1.0000.9780.5080.9961.0000.000
구매율[C/(A-B)*100]1.0000.0000.4390.0000.0001.000
2023-12-12T14:05:20.903092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총구매금액(A)(천원)제외승인(B)(천원)제외후금액(A-B)(천원)녹색구매금액(C)(천원)구매율[C/(A-B)*100]
총구매금액(A)(천원)1.0000.5020.8480.8500.259
제외승인(B)(천원)0.5021.0000.0890.112-0.007
제외후금액(A-B)(천원)0.8480.0891.0000.9950.380
녹색구매금액(C)(천원)0.8500.1120.9951.0000.443
구매율[C/(A-B)*100]0.259-0.0070.3800.4431.000

Missing values

2023-12-12T14:05:18.422773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:05:18.547179image/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

구분총구매금액(A)(천원)제외승인(B)(천원)제외후금액(A-B)(천원)녹색구매금액(C)(천원)구매율[C/(A-B)*100]
0한국전력공사1401872127789212398011416492.1
1한국전력공사 대구지역본부113653401136534111702198.3
2한국전력공사 경남지역본부2906906259349531341225144080.2
3한국전력공사 강원지역본부17027845700491132735107108994.6
4한국전력공사 전북지역본부1527469708994818475818117100.0
5한국전력공사 부산울산지역본부1547376015473761547376100.0
6한국전력공사 경기북부지역본부664900066490064622397.2
7한국전력공사 남서울지역본부148914014891413228488.8
8한국전력공사 경기지역본부998475099847598353198.5
9한국전력공사 서울지역본부629786062978658208792.4
구분총구매금액(A)(천원)제외승인(B)(천원)제외후금액(A-B)(천원)녹색구매금액(C)(천원)구매율[C/(A-B)*100]
17한국전력공사 설비진단처9970099709970100.0
18한국전력공사 ICT인프라처264970802649708264061099.7
19한국전력공사 전력기반조성사업센터135300135308806.5
20한국전력공사 수안보생활연수원435760435763649483.7
21한국전력공사 제주지역본부251615345504020611132061113100.0
22한국전력공사 경북지역본부746388074638871341395.6
23한국전력공사 업무지원처514592051459244279886.0
24한국전력공사 대전충남지역본부369718603697186363710198.4
25한국전력공사 충북지역본부683972068397266637397.4
26한국전력공사 인천지역본부851741085174181447495.6