Overview

Dataset statistics

Number of variables20
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory170.4 B

Variable types

Categorical14
Text2
Numeric4

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://bigdata-region.kr/#/dataset/6724dc75-15ed-46c4-9fd4-3b49deceabf8

Alerts

기준년월 has constant value ""Constant
등록일자 has constant value ""Constant
작업자명 has constant value ""Constant
대표자성별코드 is highly overall correlated with 대표자성별명High correlation
업력구간코드 is highly overall correlated with 업력구간명High correlation
업력구간명 is highly overall correlated with 업력구간코드High correlation
업종대분류코드 is highly overall correlated with 업종대분류명High correlation
대표자성별명 is highly overall correlated with 대표자성별코드High correlation
업종대분류명 is highly overall correlated with 업종대분류코드High correlation
대표자연령구간코드 is highly overall correlated with 대표자연령구간명High correlation
총추정매출금액 is highly overall correlated with 추정매출평균금액 and 4 other fieldsHigh correlation
추정매출평균금액 is highly overall correlated with 총추정매출금액 and 3 other fieldsHigh correlation
추정매출중위금액 is highly overall correlated with 총추정매출금액 and 1 other fieldsHigh correlation
시도명 is highly overall correlated with 총추정매출금액 and 4 other fieldsHigh correlation
시군구명 is highly overall correlated with 총추정매출금액 and 4 other fieldsHigh correlation
행정동명 is highly overall correlated with 시도명 and 1 other fieldsHigh correlation
대표자연령구간명 is highly overall correlated with 대표자연령구간코드High correlation
총기업수 is highly overall correlated with 총추정매출금액 and 2 other fieldsHigh correlation
시도명 is highly imbalanced (64.7%)Imbalance
시군구명 is highly imbalanced (64.7%)Imbalance
총추정매출금액 has 4 (13.3%) zerosZeros
추정매출평균금액 has 4 (13.3%) zerosZeros
추정매출중위금액 has 5 (16.7%) zerosZeros

Reproduction

Analysis started2023-12-10 13:59:41.715362
Analysis finished2023-12-10 13:59:51.821794
Duration10.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-05
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-05
2nd row2020-05
3rd row2020-05
4th row2020-05
5th row2020-05

Common Values

ValueCountFrequency (%)
2020-05 30
100.0%

Length

2023-12-10T22:59:51.932415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:52.091425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-05 30
100.0%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
강원
28 
충북
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원
2nd row충북
3rd row강원
4th row강원
5th row강원

Common Values

ValueCountFrequency (%)
강원 28
93.3%
충북 2
 
6.7%

Length

2023-12-10T22:59:52.249268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:52.416219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원 28
93.3%
충북 2
 
6.7%

시군구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
강릉시
28 
충주시
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강릉시
2nd row충주시
3rd row강릉시
4th row강릉시
5th row강릉시

Common Values

ValueCountFrequency (%)
강릉시 28
93.3%
충주시 2
 
6.7%

Length

2023-12-10T22:59:52.599555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:52.792654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강릉시 28
93.3%
충주시 2
 
6.7%

행정동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
교1동
14 
경포동
6 
강남동
2 
칠금.금릉동
2 
교2동
2 
Other values (3)
4 

Length

Max length6
Median length3
Mean length3.2
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row강남동
2nd row칠금.금릉동
3rd row강남동
4th row강동면
5th row경포동

Common Values

ValueCountFrequency (%)
교1동 14
46.7%
경포동 6
20.0%
강남동 2
 
6.7%
칠금.금릉동 2
 
6.7%
교2동 2
 
6.7%
내곡동 2
 
6.7%
강동면 1
 
3.3%
구정면 1
 
3.3%

Length

2023-12-10T22:59:52.985794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:53.199792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교1동 14
46.7%
경포동 6
20.0%
강남동 2
 
6.7%
칠금.금릉동 2
 
6.7%
교2동 2
 
6.7%
내곡동 2
 
6.7%
강동면 1
 
3.3%
구정면 1
 
3.3%

업종대분류코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
R
10 
S
9 
F
9 
E
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowS
3rd rowS
4th rowR
5th rowE

Common Values

ValueCountFrequency (%)
R 10
33.3%
S 9
30.0%
F 9
30.0%
E 2
 
6.7%

Length

2023-12-10T22:59:53.466331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:53.630700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
r 10
33.3%
s 9
30.0%
f 9
30.0%
e 2
 
6.7%

업종중분류코드
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:53.857284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)23.3%

Sample

1st rowR12
2nd rowS04
3rd rowS04
4th rowR12
5th rowE03
ValueCountFrequency (%)
s04 4
13.3%
f14 4
13.3%
s05 3
10.0%
r12 2
 
6.7%
e03 2
 
6.7%
f11 2
 
6.7%
r25 2
 
6.7%
f01 2
 
6.7%
r26 2
 
6.7%
s06 1
 
3.3%
Other values (6) 6
20.0%
2023-12-10T22:59:54.299562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
17.8%
1 14
15.6%
R 10
11.1%
S 9
10.0%
4 9
10.0%
F 9
10.0%
2 7
7.8%
5 5
 
5.6%
6 4
 
4.4%
3 3
 
3.3%
Other values (3) 4
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
66.7%
Uppercase Letter 30
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
26.7%
1 14
23.3%
4 9
15.0%
2 7
11.7%
5 5
 
8.3%
6 4
 
6.7%
3 3
 
5.0%
8 1
 
1.7%
7 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
R 10
33.3%
S 9
30.0%
F 9
30.0%
E 2
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 60
66.7%
Latin 30
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
26.7%
1 14
23.3%
4 9
15.0%
2 7
11.7%
5 5
 
8.3%
6 4
 
6.7%
3 3
 
5.0%
8 1
 
1.7%
7 1
 
1.7%
Latin
ValueCountFrequency (%)
R 10
33.3%
S 9
30.0%
F 9
30.0%
E 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
17.8%
1 14
15.6%
R 10
11.1%
S 9
10.0%
4 9
10.0%
F 9
10.0%
2 7
7.8%
5 5
 
5.6%
6 4
 
4.4%
3 3
 
3.3%
Other values (3) 4
 
4.4%

업종대분류명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
소매업
10 
서비스
9 
음식
9 
기타
2 

Length

Max length3
Median length3
Mean length2.6333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소매업
2nd row서비스
3rd row서비스
4th row소매업
5th row기타

Common Values

ValueCountFrequency (%)
소매업 10
33.3%
서비스 9
30.0%
음식 9
30.0%
기타 2
 
6.7%

Length

2023-12-10T22:59:54.519437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:54.699879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소매업 10
33.3%
서비스 9
30.0%
음식 9
30.0%
기타 2
 
6.7%

업종중분류명
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:54.998565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7.5
Mean length5.1666667
Min length2

Characters and Unicode

Total characters155
Distinct characters46
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

Unique7 ?
Unique (%)23.3%

Sample

1st row연료소매
2nd row생활편의서비스
3rd row생활편의서비스
4th row연료소매
5th row도매
ValueCountFrequency (%)
생활편의서비스 4
12.9%
커피/음료 4
12.9%
여가/오락서비스 3
9.7%
패션잡화 2
 
6.5%
간이주점 2
 
6.5%
화장품/미용 2
 
6.5%
제과/제빵 2
 
6.5%
도매 2
 
6.5%
연료소매 2
 
6.5%
의료서비스 1
 
3.2%
Other values (7) 7
22.6%
2023-12-10T22:59:55.551660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 12
 
7.7%
서 9
 
5.8%
비 9
 
5.8%
스 9
 
5.8%
료 8
 
5.2%
매 7
 
4.5%
의 6
 
3.9%
음 5
 
3.2%
소 5
 
3.2%
피 4
 
2.6%
Other values (36) 81
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
91.6%
Other Punctuation 12
 
7.7%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 9
 
6.3%
비 9
 
6.3%
스 9
 
6.3%
료 8
 
5.6%
매 7
 
4.9%
의 6
 
4.2%
음 5
 
3.5%
소 5
 
3.5%
피 4
 
2.8%
커 4
 
2.8%
Other values (34) 76
53.5%
Other Punctuation
ValueCountFrequency (%)
/ 12
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
91.6%
Common 13
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 9
 
6.3%
비 9
 
6.3%
스 9
 
6.3%
료 8
 
5.6%
매 7
 
4.9%
의 6
 
4.2%
음 5
 
3.5%
소 5
 
3.5%
피 4
 
2.8%
커 4
 
2.8%
Other values (34) 76
53.5%
Common
ValueCountFrequency (%)
/ 12
92.3%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
91.6%
ASCII 13
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 12
92.3%
1
 
7.7%
Hangul
ValueCountFrequency (%)
서 9
 
6.3%
비 9
 
6.3%
스 9
 
6.3%
료 8
 
5.6%
매 7
 
4.9%
의 6
 
4.2%
음 5
 
3.5%
소 5
 
3.5%
피 4
 
2.8%
커 4
 
2.8%
Other values (34) 76
53.5%

대표자성별코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
M
19 
F
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowF
5th rowM

Common Values

ValueCountFrequency (%)
M 19
63.3%
F 11
36.7%

Length

2023-12-10T22:59:55.760051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:55.930537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 19
63.3%
f 11
36.7%

대표자성별명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
남성
19 
여성
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남성
2nd row남성
3rd row여성
4th row여성
5th row남성

Common Values

ValueCountFrequency (%)
남성 19
63.3%
여성 11
36.7%

Length

2023-12-10T22:59:56.395948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:56.559817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남성 19
63.3%
여성 11
36.7%

대표자연령구간코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48
Minimum20
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:56.693562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile34.5
Q140
median50
Q360
95-th percentile65.5
Maximum70
Range50
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.566897
Coefficient of variation (CV)0.24097702
Kurtosis-0.061031569
Mean48
Median Absolute Deviation (MAD)10
Skewness-0.011459241
Sum1440
Variance133.7931
MonotonicityNot monotonic
2023-12-10T22:59:56.876475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
40 12
40.0%
50 7
23.3%
60 7
23.3%
70 2
 
6.7%
20 1
 
3.3%
30 1
 
3.3%
ValueCountFrequency (%)
20 1
 
3.3%
30 1
 
3.3%
40 12
40.0%
50 7
23.3%
60 7
23.3%
70 2
 
6.7%
ValueCountFrequency (%)
70 2
 
6.7%
60 7
23.3%
50 7
23.3%
40 12
40.0%
30 1
 
3.3%
20 1
 
3.3%

대표자연령구간명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
40대
12 
50대
7 
60대
7 
70대
2 
20대
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row50대
2nd row50대
3rd row60대
4th row40대
5th row60대

Common Values

ValueCountFrequency (%)
40대 12
40.0%
50대 7
23.3%
60대 7
23.3%
70대 2
 
6.7%
20대 1
 
3.3%
30대 1
 
3.3%

Length

2023-12-10T22:59:57.031861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:57.189956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40대 12
40.0%
50대 7
23.3%
60대 7
23.3%
70대 2
 
6.7%
20대 1
 
3.3%
30대 1
 
3.3%

업력구간코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
8 
10
7 
20
5 
5
5 
1
5 

Length

Max length2
Median length1
Mean length1.4
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row20
4th row5
5th row10

Common Values

ValueCountFrequency (%)
2 8
26.7%
10 7
23.3%
20 5
16.7%
5 5
16.7%
1 5
16.7%

Length

2023-12-10T22:59:57.426739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:57.685791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8
26.7%
10 7
23.3%
20 5
16.7%
5 5
16.7%
1 5
16.7%

업력구간명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2년 이상 5년 미만
8 
10년 이상 20년 미만
7 
20년 이상 30년 미만
5 
5년 이상 10년 미만
5 
1년 이상 2년 미만
5 

Length

Max length13
Median length12
Mean length11.966667
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20년 이상 30년 미만
2nd row20년 이상 30년 미만
3rd row20년 이상 30년 미만
4th row5년 이상 10년 미만
5th row10년 이상 20년 미만

Common Values

ValueCountFrequency (%)
2년 이상 5년 미만 8
26.7%
10년 이상 20년 미만 7
23.3%
20년 이상 30년 미만 5
16.7%
5년 이상 10년 미만 5
16.7%
1년 이상 2년 미만 5
16.7%

Length

2023-12-10T22:59:57.889191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:58.072260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이상 30
25.0%
미만 30
25.0%
2년 13
10.8%
5년 13
10.8%
10년 12
 
10.0%
20년 12
 
10.0%
30년 5
 
4.2%
1년 5
 
4.2%

총기업수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
15 
2
7 
3
5 
5
2 
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1
2nd row5
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 15
50.0%
2 7
23.3%
3 5
 
16.7%
5 2
 
6.7%
6 1
 
3.3%

Length

2023-12-10T22:59:58.258554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:58.421991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 15
50.0%
2 7
23.3%
3 5
 
16.7%
5 2
 
6.7%
6 1
 
3.3%

총추정매출금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19336.467
Minimum0
Maximum294221
Zeros4
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:58.585328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11378.5
median5291.5
Q316163.25
95-th percentile47803.1
Maximum294221
Range294221
Interquartile range (IQR)14784.75

Descriptive statistics

Standard deviation53508.167
Coefficient of variation (CV)2.7672153
Kurtosis26.232206
Mean19336.467
Median Absolute Deviation (MAD)5276
Skewness5.0039015
Sum580094
Variance2.8631239 × 109
MonotonicityNot monotonic
2023-12-10T22:59:58.774719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 4
 
13.3%
61016 1
 
3.3%
21122 1
 
3.3%
2052 1
 
3.3%
5398 1
 
3.3%
6121 1
 
3.3%
605 1
 
3.3%
18370 1
 
3.3%
1572 1
 
3.3%
13746 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0 4
13.3%
31 1
 
3.3%
329 1
 
3.3%
605 1
 
3.3%
1314 1
 
3.3%
1572 1
 
3.3%
1804 1
 
3.3%
2052 1
 
3.3%
2063 1
 
3.3%
3517 1
 
3.3%
ValueCountFrequency (%)
294221 1
3.3%
61016 1
3.3%
31654 1
3.3%
23466 1
3.3%
22563 1
3.3%
21122 1
3.3%
18370 1
3.3%
16168 1
3.3%
16149 1
3.3%
13746 1
3.3%

추정매출평균금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7515.4333
Minimum0
Maximum61016
Zeros4
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:58.983955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1782.25
median3595.5
Q35697.25
95-th percentile34245.4
Maximum61016
Range61016
Interquartile range (IQR)4915

Descriptive statistics

Standard deviation13708.753
Coefficient of variation (CV)1.8240802
Kurtosis10.121508
Mean7515.4333
Median Absolute Deviation (MAD)2595
Skewness3.1772314
Sum225463
Variance1.8792991 × 108
MonotonicityNot monotonic
2023-12-10T22:59:59.314928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 4
 
13.3%
61016 1
 
3.3%
10561 1
 
3.3%
2052 1
 
3.3%
2699 1
 
3.3%
2040 1
 
3.3%
605 1
 
3.3%
3674 1
 
3.3%
524 1
 
3.3%
4582 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0 4
13.3%
31 1
 
3.3%
164 1
 
3.3%
524 1
 
3.3%
605 1
 
3.3%
1314 1
 
3.3%
1804 1
 
3.3%
2040 1
 
3.3%
2052 1
 
3.3%
2063 1
 
3.3%
ValueCountFrequency (%)
61016 1
3.3%
49036 1
3.3%
16168 1
3.3%
15827 1
3.3%
11281 1
3.3%
10561 1
3.3%
6504 1
3.3%
5802 1
3.3%
5383 1
3.3%
5185 1
3.3%

추정매출중위금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6183.8333
Minimum0
Maximum61016
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:59.533140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1606.5
median2392.5
Q35938.5
95-th percentile16466.65
Maximum61016
Range61016
Interquartile range (IQR)5332

Descriptive statistics

Standard deviation11503.559
Coefficient of variation (CV)1.8602634
Kurtosis18.672591
Mean6183.8333
Median Absolute Deviation (MAD)2377
Skewness4.0166664
Sum185515
Variance1.3233186 × 108
MonotonicityNot monotonic
2023-12-10T22:59:59.747694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 5
 
16.7%
61016 1
 
3.3%
3517 1
 
3.3%
2052 1
 
3.3%
2699 1
 
3.3%
792 1
 
3.3%
605 1
 
3.3%
3800 1
 
3.3%
611 1
 
3.3%
16168 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0 5
16.7%
31 1
 
3.3%
164 1
 
3.3%
605 1
 
3.3%
611 1
 
3.3%
792 1
 
3.3%
1314 1
 
3.3%
1804 1
 
3.3%
2052 1
 
3.3%
2063 1
 
3.3%
ValueCountFrequency (%)
61016 1
3.3%
16711 1
3.3%
16168 1
3.3%
15827 1
3.3%
11281 1
3.3%
10561 1
3.3%
6504 1
3.3%
5984 1
3.3%
5802 1
3.3%
5185 1
3.3%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-11-18
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-11-18
2nd row2021-11-18
3rd row2021-11-18
4th row2021-11-18
5th row2021-11-18

Common Values

ValueCountFrequency (%)
2021-11-18 30
100.0%

Length

2023-12-10T22:59:59.972704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:00:00.180722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-11-18 30
100.0%

작업자명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
kedsystem
30 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kedsystem 30
100.0%

Length

2023-12-10T23:00:00.358491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:00:00.540751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kedsystem 30
100.0%

Interactions

2023-12-10T22:59:50.553734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:48.637255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.235782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.832723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:50.766132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:48.836924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.377809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.979946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:50.927440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:48.968753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.533067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:50.173074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:51.061867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.099330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:49.678411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:50.407249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:00:00.654504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명행정동명업종대분류코드업종중분류코드업종대분류명업종중분류명대표자성별코드대표자성별명대표자연령구간코드대표자연령구간명업력구간코드업력구간명총기업수총추정매출금액추정매출평균금액추정매출중위금액
시도명1.0000.9061.0000.4060.5600.4060.5600.0000.0000.0000.0000.0000.0000.6970.8540.5280.276
시군구명0.9061.0001.0000.4060.5600.4060.5600.0000.0000.0000.0000.0000.0000.6970.8540.5280.276
행정동명1.0001.0001.0000.7050.0000.7050.0000.0000.0000.3260.3260.4630.4630.2790.7480.3920.338
업종대분류코드0.4060.4060.7051.0001.0001.0001.0000.1830.1830.3410.3410.0000.0000.4730.0000.1610.286
업종중분류코드0.5600.5600.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.7540.8450.8510.821
업종대분류명0.4060.4060.7051.0001.0001.0001.0000.1830.1830.3410.3410.0000.0000.4730.0000.1610.286
업종중분류명0.5600.5600.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.7540.8450.8510.821
대표자성별코드0.0000.0000.0000.1830.0000.1830.0001.0000.9930.0000.0000.0000.0000.0920.0000.0130.156
대표자성별명0.0000.0000.0000.1830.0000.1830.0000.9931.0000.0000.0000.0000.0000.0920.0000.0130.156
대표자연령구간코드0.0000.0000.3260.3410.0000.3410.0000.0000.0001.0001.0000.0000.0000.0000.0000.0000.000
대표자연령구간명0.0000.0000.3260.3410.0000.3410.0000.0000.0001.0001.0000.0000.0000.0000.0000.0000.000
업력구간코드0.0000.0000.4630.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.0000.0430.0000.155
업력구간명0.0000.0000.4630.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.0000.0430.0000.155
총기업수0.6970.6970.2790.4730.7540.4730.7540.0920.0920.0000.0000.0000.0001.0000.6070.8150.242
총추정매출금액0.8540.8540.7480.0000.8450.0000.8450.0000.0000.0000.0000.0430.0430.6071.0000.8950.952
추정매출평균금액0.5280.5280.3920.1610.8510.1610.8510.0130.0130.0000.0000.0000.0000.8150.8951.0001.000
추정매출중위금액0.2760.2760.3380.2860.8210.2860.8210.1560.1560.0000.0000.1550.1550.2420.9521.0001.000
2023-12-10T23:00:01.018947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총기업수시군구명대표자성별코드대표자연령구간명업력구간코드행정동명업력구간명시도명업종대분류코드대표자성별명업종대분류명
총기업수1.0000.7840.0810.0000.0000.1330.0000.7840.3890.0810.389
시군구명0.7841.0000.0000.0000.0000.8860.0000.7210.2560.0000.256
대표자성별코드0.0810.0001.0000.0000.0000.0000.0000.0000.1010.9260.101
대표자연령구간명0.0000.0000.0001.0000.0000.1510.0000.0000.2020.0000.202
업력구간코드0.0000.0000.0000.0001.0000.2721.0000.0000.0000.0000.000
행정동명0.1330.8860.0000.1510.2721.0000.2720.8860.3380.0000.338
업력구간명0.0000.0000.0000.0001.0000.2721.0000.0000.0000.0000.000
시도명0.7840.7210.0000.0000.0000.8860.0001.0000.2560.0000.256
업종대분류코드0.3890.2560.1010.2020.0000.3380.0000.2561.0000.1011.000
대표자성별명0.0810.0000.9260.0000.0000.0000.0000.0000.1011.0000.101
업종대분류명0.3890.2560.1010.2020.0000.3380.0000.2561.0000.1011.000
2023-12-10T23:00:01.449192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표자연령구간코드총추정매출금액추정매출평균금액추정매출중위금액시도명시군구명행정동명업종대분류코드업종대분류명대표자성별코드대표자성별명대표자연령구간명업력구간코드업력구간명총기업수
대표자연령구간코드1.000-0.174-0.322-0.1810.0000.0000.1510.2020.2020.0000.0001.0000.0000.0000.000
총추정매출금액-0.1741.0000.9360.8380.6280.6280.3730.0000.0000.0000.0000.0000.0000.0000.521
추정매출평균금액-0.3220.9361.0000.9280.6020.6020.2180.1080.1080.0000.0000.0000.0000.0000.435
추정매출중위금액-0.1810.8380.9281.0000.1670.1670.1090.0970.0970.0800.0800.0000.1020.1020.183
시도명0.0000.6280.6020.1671.0000.7210.8860.2560.2560.0000.0000.0000.0000.0000.784
시군구명0.0000.6280.6020.1670.7211.0000.8860.2560.2560.0000.0000.0000.0000.0000.784
행정동명0.1510.3730.2180.1090.8860.8861.0000.3380.3380.0000.0000.1510.2720.2720.133
업종대분류코드0.2020.0000.1080.0970.2560.2560.3381.0001.0000.1010.1010.2020.0000.0000.389
업종대분류명0.2020.0000.1080.0970.2560.2560.3381.0001.0000.1010.1010.2020.0000.0000.389
대표자성별코드0.0000.0000.0000.0800.0000.0000.0000.1010.1011.0000.9260.0000.0000.0000.081
대표자성별명0.0000.0000.0000.0800.0000.0000.0000.1010.1010.9261.0000.0000.0000.0000.081
대표자연령구간명1.0000.0000.0000.0000.0000.0000.1510.2020.2020.0000.0001.0000.0000.0000.000
업력구간코드0.0000.0000.0000.1020.0000.0000.2720.0000.0000.0000.0000.0001.0001.0000.000
업력구간명0.0000.0000.0000.1020.0000.0000.2720.0000.0000.0000.0000.0001.0001.0000.000
총기업수0.0000.5210.4350.1830.7840.7840.1330.3890.3890.0810.0810.0000.0000.0001.000

Missing values

2023-12-10T22:59:51.282657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:59:51.667737image/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

기준년월시도명시군구명행정동명업종대분류코드업종중분류코드업종대분류명업종중분류명대표자성별코드대표자성별명대표자연령구간코드대표자연령구간명업력구간코드업력구간명총기업수총추정매출금액추정매출평균금액추정매출중위금액등록일자작업자명
02020-05강원강릉시강남동RR12소매업연료소매M남성5050대2020년 이상 30년 미만16101661016610162021-11-18kedsystem
12020-05충북충주시칠금.금릉동SS04서비스생활편의서비스M남성5050대2020년 이상 30년 미만523466469320862021-11-18kedsystem
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