Overview

Dataset statistics

Number of variables4
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory36.1 B

Variable types

Text1
Numeric3

Dataset

Description한국남동발전의 친환경 제품 구매 실적 현황 자료 입니다. 각 항목(분류) 별 총 구매 금액, 녹색 구매 금액, 비율 등의 정보를 포함하고 있습니다.
Author한국남동발전㈜
URLhttps://www.data.go.kr/data/15060700/fileData.do

Alerts

총구매금액(천원) is highly overall correlated with 녹색구매금액(천원) and 1 other fieldsHigh correlation
녹색구매금액(천원) is highly overall correlated with 총구매금액(천원) and 1 other fieldsHigh correlation
비율 is highly overall correlated with 총구매금액(천원) and 1 other fieldsHigh correlation
분류 has unique valuesUnique
총구매금액(천원) has 94 (75.8%) zerosZeros
녹색구매금액(천원) has 100 (80.6%) zerosZeros
비율 has 100 (80.6%) zerosZeros

Reproduction

Analysis started2023-12-12 18:20:47.642116
Analysis finished2023-12-12 18:20:48.739278
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Text

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T03:20:48.944995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.016129
Min length2

Characters and Unicode

Total characters746
Distinct characters205
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)100.0%

Sample

1st row복사기
2nd row식기세척기
3rd row공기청정기
4th row텔레비전 및 비디오프로젝터
5th row책상(탁자)
ValueCountFrequency (%)
및 19
 
9.2%
기타 13
 
6.3%
산업용 2
 
1.0%
건설용 2
 
1.0%
수도꼭지 2
 
1.0%
수도계량기 2
 
1.0%
벽 2
 
1.0%
필기구 2
 
1.0%
의복 2
 
1.0%
절수형 2
 
1.0%
Other values (153) 158
76.7%
2023-12-13T03:20:49.357547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
11.0%
기 41
 
5.5%
용 24
 
3.2%
및 19
 
2.5%
타 19
 
2.5%
수 15
 
2.0%
장 14
 
1.9%
재 14
 
1.9%
지 13
 
1.7%
품 13
 
1.7%
Other values (195) 492
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 653
87.5%
Space Separator 82
 
11.0%
Other Punctuation 5
 
0.7%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 41
 
6.3%
용 24
 
3.7%
및 19
 
2.9%
타 19
 
2.9%
수 15
 
2.3%
장 14
 
2.1%
재 14
 
2.1%
지 13
 
2.0%
품 13
 
2.0%
비 10
 
1.5%
Other values (187) 471
72.1%
Other Punctuation
ValueCountFrequency (%)
/ 3
60.0%
· 1
 
20.0%
, 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 653
87.5%
Common 91
 
12.2%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 41
 
6.3%
용 24
 
3.7%
및 19
 
2.9%
타 19
 
2.9%
수 15
 
2.3%
장 14
 
2.1%
재 14
 
2.1%
지 13
 
2.0%
품 13
 
2.0%
비 10
 
1.5%
Other values (187) 471
72.1%
Common
ValueCountFrequency (%)
82
90.1%
/ 3
 
3.3%
) 2
 
2.2%
( 2
 
2.2%
· 1
 
1.1%
, 1
 
1.1%
Latin
ValueCountFrequency (%)
A 1
50.0%
O 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 653
87.5%
ASCII 92
 
12.3%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
89.1%
/ 3
 
3.3%
) 2
 
2.2%
( 2
 
2.2%
, 1
 
1.1%
A 1
 
1.1%
O 1
 
1.1%
Hangul
ValueCountFrequency (%)
기 41
 
6.3%
용 24
 
3.7%
및 19
 
2.9%
타 19
 
2.9%
수 15
 
2.3%
장 14
 
2.1%
재 14
 
2.1%
지 13
 
2.0%
품 13
 
2.0%
비 10
 
1.5%
Other values (187) 471
72.1%
None
ValueCountFrequency (%)
· 1
100.0%

총구매금액(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37503.911
Minimum0
Maximum841422
Zeros94
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T03:20:49.870021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile231775.95
Maximum841422
Range841422
Interquartile range (IQR)0

Descriptive statistics

Standard deviation125645.52
Coefficient of variation (CV)3.3501977
Kurtosis23.05117
Mean37503.911
Median Absolute Deviation (MAD)0
Skewness4.5730572
Sum4650485
Variance1.5786796 × 1010
MonotonicityNot monotonic
2023-12-13T03:20:50.029123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 94
75.8%
10438 1
 
0.8%
4436 1
 
0.8%
9110 1
 
0.8%
36053 1
 
0.8%
85924 1
 
0.8%
39222 1
 
0.8%
10826 1
 
0.8%
512415 1
 
0.8%
24960 1
 
0.8%
Other values (21) 21
 
16.9%
ValueCountFrequency (%)
0 94
75.8%
456 1
 
0.8%
1511 1
 
0.8%
1960 1
 
0.8%
2187 1
 
0.8%
4436 1
 
0.8%
9110 1
 
0.8%
10438 1
 
0.8%
10826 1
 
0.8%
14615 1
 
0.8%
ValueCountFrequency (%)
841422 1
0.8%
753492 1
0.8%
512415 1
0.8%
380418 1
0.8%
337332 1
0.8%
309945 1
0.8%
232800 1
0.8%
225973 1
0.8%
200865 1
0.8%
155624 1
0.8%

녹색구매금액(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24293.952
Minimum0
Maximum841422
Zeros100
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T03:20:50.232608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile147937.05
Maximum841422
Range841422
Interquartile range (IQR)0

Descriptive statistics

Standard deviation93861.31
Coefficient of variation (CV)3.863567
Kurtosis48.758983
Mean24293.952
Median Absolute Deviation (MAD)0
Skewness6.3397637
Sum3012450
Variance8.8099455 × 109
MonotonicityNot monotonic
2023-12-13T03:20:50.374117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 100
80.6%
10438 1
 
0.8%
85924 1
 
0.8%
18330 1
 
0.8%
46310 1
 
0.8%
24960 1
 
0.8%
841422 1
 
0.8%
23513 1
 
0.8%
48082 1
 
0.8%
65466 1
 
0.8%
Other values (15) 15
 
12.1%
ValueCountFrequency (%)
0 100
80.6%
199 1
 
0.8%
1511 1
 
0.8%
1960 1
 
0.8%
10438 1
 
0.8%
14615 1
 
0.8%
18330 1
 
0.8%
19448 1
 
0.8%
23513 1
 
0.8%
24960 1
 
0.8%
ValueCountFrequency (%)
841422 1
0.8%
364138 1
0.8%
317322 1
0.8%
232800 1
0.8%
218292 1
0.8%
200865 1
0.8%
151506 1
0.8%
127713 1
0.8%
98337 1
0.8%
85924 1
0.8%

비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.475806
Minimum0
Maximum100
Zeros100
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T03:20:50.499869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation35.77742
Coefficient of variation (CV)2.1715125
Kurtosis1.422728
Mean16.475806
Median Absolute Deviation (MAD)0
Skewness1.8146251
Sum2043
Variance1280.0238
MonotonicityNot monotonic
2023-12-13T03:20:50.648693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 100
80.6%
100 13
 
10.5%
97 2
 
1.6%
94 1
 
0.8%
91 1
 
0.8%
89 1
 
0.8%
44 1
 
0.8%
58 1
 
0.8%
96 1
 
0.8%
21 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 100
80.6%
9 1
 
0.8%
21 1
 
0.8%
44 1
 
0.8%
47 1
 
0.8%
58 1
 
0.8%
89 1
 
0.8%
91 1
 
0.8%
94 1
 
0.8%
96 1
 
0.8%
ValueCountFrequency (%)
100 13
10.5%
97 2
 
1.6%
96 1
 
0.8%
94 1
 
0.8%
91 1
 
0.8%
89 1
 
0.8%
58 1
 
0.8%
47 1
 
0.8%
44 1
 
0.8%
21 1
 
0.8%

Interactions

2023-12-13T03:20:48.308678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:47.806401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:48.062418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:48.389393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:47.893228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:48.138352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:48.476214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:47.978783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:20:48.230391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:20:50.751872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총구매금액(천원)녹색구매금액(천원)비율
총구매금액(천원)1.0000.9550.749
녹색구매금액(천원)0.9551.0000.691
비율0.7490.6911.000
2023-12-13T03:20:50.880106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총구매금액(천원)녹색구매금액(천원)비율
총구매금액(천원)1.0000.8860.868
녹색구매금액(천원)0.8861.0000.985
비율0.8680.9851.000

Missing values

2023-12-13T03:20:48.607443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:20:48.702378image/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

분류총구매금액(천원)녹색구매금액(천원)비율
0복사기1043810438100
1식기세척기443600
2공기청정기218700
3텔레비전 및 비디오프로젝터33733231732294
4책상(탁자)805987335591
5의자14374812771389
6보관용 가구15562415150697
7주방가구1944819448100
8기타 가구 및 부속품45619944
9OA칸막이447752594458
분류총구매금액(천원)녹색구매금액(천원)비율
114레미콘000
115인쇄용지000
116난방연료000
117영상감시장치000
118절수형 양변기000
119열연강판/후판000
120절수형 수도꼭지000
121침대 및 침대매트릭스000
122사료000
123기타000