Overview

Dataset statistics

Number of variables5
Number of observations570
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.9 KiB
Average record size in memory41.2 B

Variable types

Numeric1
Text1
Categorical2
Boolean1

Dataset

Description환경컨설팅 서비스를 제공하는 컨설턴트의 전문분야 정보(컨설턴트아이디, 분야명, 삭제여부, 컨설턴트/전문인력 구분)를 제공합니다.
Author환경부
URLhttps://www.data.go.kr/data/15039235/fileData.do

Alerts

삭제여부 has constant value ""Constant
연번 is highly overall correlated with 구분High correlation
분야명 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 15:02:58.438920
Analysis finished2024-04-21 15:02:59.144174
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct570
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean865.21053
Minimum561
Maximum1275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-22T00:02:59.271422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum561
5-th percentile592.45
Q1720.25
median862.5
Q31004.75
95-th percentile1118.55
Maximum1275
Range714
Interquartile range (IQR)284.5

Descriptive statistics

Standard deviation176.3069
Coefficient of variation (CV)0.20377342
Kurtosis-0.80397876
Mean865.21053
Median Absolute Deviation (MAD)142.5
Skewness0.16618992
Sum493170
Variance31084.124
MonotonicityNot monotonic
2024-04-22T00:02:59.530680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
747 1
 
0.2%
1258 1
 
0.2%
1194 1
 
0.2%
1195 1
 
0.2%
1223 1
 
0.2%
1229 1
 
0.2%
1230 1
 
0.2%
1235 1
 
0.2%
1259 1
 
0.2%
1122 1
 
0.2%
Other values (560) 560
98.2%
ValueCountFrequency (%)
561 1
0.2%
562 1
0.2%
563 1
0.2%
564 1
0.2%
565 1
0.2%
566 1
0.2%
567 1
0.2%
569 1
0.2%
571 1
0.2%
572 1
0.2%
ValueCountFrequency (%)
1275 1
0.2%
1274 1
0.2%
1269 1
0.2%
1268 1
0.2%
1267 1
0.2%
1266 1
0.2%
1265 1
0.2%
1262 1
0.2%
1261 1
0.2%
1260 1
0.2%

컨설턴트아이디(전문인력번호)
Text

Distinct344
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-04-22T00:03:00.472345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4.1578947
Min length3

Characters and Unicode

Total characters2370
Distinct characters50
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)35.1%

Sample

1st row442
2nd row443
3rd row443
4th row443
5th row443
ValueCountFrequency (%)
431 6
 
1.1%
468 6
 
1.1%
676 5
 
0.9%
675 5
 
0.9%
426 4
 
0.7%
658 4
 
0.7%
482 4
 
0.7%
486 4
 
0.7%
646 4
 
0.7%
487 4
 
0.7%
Other values (334) 524
91.9%
2024-04-22T00:03:01.610839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 276
 
11.6%
4 238
 
10.0%
5 166
 
7.0%
7 156
 
6.6%
0 137
 
5.8%
8 130
 
5.5%
1 114
 
4.8%
2 113
 
4.8%
3 112
 
4.7%
9 89
 
3.8%
Other values (40) 839
35.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1531
64.6%
Lowercase Letter 824
34.8%
Uppercase Letter 7
 
0.3%
Other Letter 5
 
0.2%
Dash Punctuation 2
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 67
 
8.1%
o 62
 
7.5%
s 60
 
7.3%
e 59
 
7.2%
h 58
 
7.0%
k 57
 
6.9%
a 56
 
6.8%
i 48
 
5.8%
m 40
 
4.9%
u 39
 
4.7%
Other values (16) 278
33.7%
Decimal Number
ValueCountFrequency (%)
6 276
18.0%
4 238
15.5%
5 166
10.8%
7 156
10.2%
0 137
8.9%
8 130
8.5%
1 114
7.4%
2 113
7.4%
3 112
7.3%
9 89
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
R 1
14.3%
A 1
14.3%
Y 1
14.3%
O 1
14.3%
C 1
14.3%
I 1
14.3%
K 1
14.3%
Other Letter
ValueCountFrequency (%)
대 1
20.0%
재 1
20.0%
선 1
20.0%
이 1
20.0%
기 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1534
64.7%
Latin 831
35.1%
Hangul 5
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 67
 
8.1%
o 62
 
7.5%
s 60
 
7.2%
e 59
 
7.1%
h 58
 
7.0%
k 57
 
6.9%
a 56
 
6.7%
i 48
 
5.8%
m 40
 
4.8%
u 39
 
4.7%
Other values (23) 285
34.3%
Common
ValueCountFrequency (%)
6 276
18.0%
4 238
15.5%
5 166
10.8%
7 156
10.2%
0 137
8.9%
8 130
8.5%
1 114
7.4%
2 113
7.4%
3 112
7.3%
9 89
 
5.8%
Other values (2) 3
 
0.2%
Hangul
ValueCountFrequency (%)
대 1
20.0%
재 1
20.0%
선 1
20.0%
이 1
20.0%
기 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2365
99.8%
Hangul 5
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 276
 
11.7%
4 238
 
10.1%
5 166
 
7.0%
7 156
 
6.6%
0 137
 
5.8%
8 130
 
5.5%
1 114
 
4.8%
2 113
 
4.8%
3 112
 
4.7%
9 89
 
3.8%
Other values (35) 834
35.3%
Hangul
ValueCountFrequency (%)
대 1
20.0%
재 1
20.0%
선 1
20.0%
이 1
20.0%
기 1
20.0%

분야명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
환경경영
101 
기타
86 
기후변화대책
61 
환경영향평가
51 
오염방지기술
48 
Other values (26)
223 

Length

Max length9
Median length7
Mean length4.4789474
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row환경신기술평가
2nd row대기총량규제
3rd row환경분쟁조정
4th row환경신기술평가
5th row오염방지기술

Common Values

ValueCountFrequency (%)
환경경영 101
17.7%
기타 86
15.1%
기후변화대책 61
10.7%
환경영향평가 51
 
8.9%
오염방지기술 48
 
8.4%
대기총량규제 29
 
5.1%
환경신기술평가 23
 
4.0%
폐수 16
 
2.8%
기타컨설팅 15
 
2.6%
친환경개발 12
 
2.1%
Other values (21) 128
22.5%

Length

2024-04-22T00:03:01.854548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환경경영 101
17.7%
기타 86
15.1%
기후변화대책 61
10.7%
환경영향평가 51
 
8.9%
오염방지기술 48
 
8.4%
대기총량규제 29
 
5.1%
환경신기술평가 23
 
4.0%
폐수 16
 
2.8%
기타컨설팅 15
 
2.6%
친환경개발 12
 
2.1%
Other values (21) 128
22.5%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size698.0 B
False
570 
ValueCountFrequency (%)
False 570
100.0%
2024-04-22T00:03:02.027003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
전문인력
422 
컨설턴트
148 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전문인력 422
74.0%
컨설턴트 148
 
26.0%

Length

2024-04-22T00:03:02.191123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:03:02.351753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문인력 422
74.0%
컨설턴트 148
 
26.0%

Interactions

2024-04-22T00:02:58.704684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T00:03:02.458941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분야명구분
연번1.0000.7561.000
분야명0.7561.0000.958
구분1.0000.9581.000
2024-04-22T00:03:02.603539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야명구분
분야명1.0000.890
구분0.8901.000
2024-04-22T00:03:02.740792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분야명구분
연번1.0000.3760.984
분야명0.3761.0000.890
구분0.9840.8901.000

Missing values

2024-04-22T00:02:58.914907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T00:02:59.078260image/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

연번컨설턴트아이디(전문인력번호)분야명삭제여부구분
0747442환경신기술평가N전문인력
1748443대기총량규제N전문인력
2749443환경분쟁조정N전문인력
3750443환경신기술평가N전문인력
4751443오염방지기술N전문인력
5752444환경신기술평가N전문인력
6753444오염방지기술N전문인력
7754445환경신기술평가N전문인력
8755445친환경상품인증N전문인력
9756446환경영향평가N전문인력
연번컨설턴트아이디(전문인력번호)분야명삭제여부구분
560737435오염방지기술N전문인력
561738436환경경영N전문인력
562739437측정기술N전문인력
563740438대기총량규제N전문인력
564741438오염방지기술N전문인력
565742439환경신기술평가N전문인력
566743439오염방지기술N전문인력
567744439측정기술N전문인력
568745440측정기술N전문인력
569746442신규화학물질N전문인력