Overview

Dataset statistics

Number of variables11
Number of observations400
Missing cells400
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.8 KiB
Average record size in memory94.3 B

Variable types

Categorical5
Unsupported1
Numeric3
Text1
DateTime1

Dataset

DescriptionSample
Author소상공인연합회
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=KFMZEROSTT002

Alerts

소상공인결제분류코드 has constant value ""Constant
년월 has constant value ""Constant
광역시도코드 has constant value ""Constant
광역시도명 has constant value ""Constant
소상공인시스템로그일시 has constant value ""Constant
결제건수 is highly overall correlated with 합계금액High correlation
합계금액 is highly overall correlated with 결제건수High correlation
표준산업업종상세분류코드 is highly overall correlated with 표준산업업종대분류코드High correlation
표준산업업종대분류코드 is highly overall correlated with 표준산업업종상세분류코드High correlation
소상공인시스템로그ID has 400 (100.0%) missing valuesMissing
표준산업업종상세분류코드 has unique valuesUnique
표준산업업종상세분류명 has unique valuesUnique
소상공인시스템로그ID is an unsupported type, check if it needs cleaning or further analysisUnsupported
결제건수 has 317 (79.2%) zerosZeros
합계금액 has 317 (79.2%) zerosZeros

Reproduction

Analysis started2023-12-10 06:24:56.848470
Analysis finished2023-12-10 06:24:59.297975
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소상공인결제분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
ZEROP41000
400 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowZEROP41000
2nd rowZEROP41000
3rd rowZEROP41000
4th rowZEROP41000
5th rowZEROP41000

Common Values

ValueCountFrequency (%)
ZEROP41000 400
100.0%

Length

2023-12-10T15:24:59.396895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:24:59.548774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
zerop41000 400
100.0%

년월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
202008
400 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202008
2nd row202008
3rd row202008
4th row202008
5th row202008

Common Values

ValueCountFrequency (%)
202008 400
100.0%

Length

2023-12-10T15:24:59.739593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:24:59.909365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202008 400
100.0%

소상공인시스템로그ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing400
Missing (%)100.0%
Memory size3.6 KiB

광역시도코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
41
400 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41
2nd row41
3rd row41
4th row41
5th row41

Common Values

ValueCountFrequency (%)
41 400
100.0%

Length

2023-12-10T15:25:00.411471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:00.599349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41 400
100.0%

광역시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
경기도
400 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 400
100.0%

Length

2023-12-10T15:25:00.790745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:01.000374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 400
100.0%

결제건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2175
Minimum0
Maximum300
Zeros317
Zeros (%)79.2%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:25:01.155505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum300
Range300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.319631
Coefficient of variation (CV)6.3153477
Kurtosis139.38062
Mean3.2175
Median Absolute Deviation (MAD)0
Skewness10.994597
Sum1287
Variance412.88741
MonotonicityNot monotonic
2023-12-10T15:25:01.374287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 317
79.2%
1 30
 
7.5%
2 11
 
2.8%
3 8
 
2.0%
4 6
 
1.5%
7 6
 
1.5%
6 3
 
0.8%
15 2
 
0.5%
24 2
 
0.5%
34 1
 
0.2%
Other values (14) 14
 
3.5%
ValueCountFrequency (%)
0 317
79.2%
1 30
 
7.5%
2 11
 
2.8%
3 8
 
2.0%
4 6
 
1.5%
5 1
 
0.2%
6 3
 
0.8%
7 6
 
1.5%
8 1
 
0.2%
13 1
 
0.2%
ValueCountFrequency (%)
300 1
0.2%
200 1
0.2%
124 1
0.2%
80 1
0.2%
75 1
0.2%
46 1
0.2%
41 1
0.2%
38 1
0.2%
36 1
0.2%
34 1
0.2%

합계금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct70
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1219284.4
Minimum0
Maximum2.37482 × 108
Zeros317
Zeros (%)79.2%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:25:01.617129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile430889
Maximum2.37482 × 108
Range2.37482 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13987107
Coefficient of variation (CV)11.47157
Kurtosis221.6829
Mean1219284.4
Median Absolute Deviation (MAD)0
Skewness14.306275
Sum4.8771378 × 108
Variance1.9563916 × 1014
MonotonicityNot monotonic
2023-12-10T15:25:01.913903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 317
79.2%
1 10
 
2.5%
10000 3
 
0.8%
3 2
 
0.5%
30000 2
 
0.5%
12000 2
 
0.5%
1364900 1
 
0.2%
165300 1
 
0.2%
106500 1
 
0.2%
97000 1
 
0.2%
Other values (60) 60
 
15.0%
ValueCountFrequency (%)
0 317
79.2%
1 10
 
2.5%
3 2
 
0.5%
100 1
 
0.2%
1000 1
 
0.2%
2500 1
 
0.2%
3801 1
 
0.2%
4000 1
 
0.2%
5000 1
 
0.2%
8000 1
 
0.2%
ValueCountFrequency (%)
237482001 1
0.2%
122930000 1
0.2%
83150000 1
0.2%
12153007 1
0.2%
7013901 1
0.2%
3018700 1
0.2%
2339300 1
0.2%
2087100 1
0.2%
1983990 1
0.2%
1670000 1
0.2%

표준산업업종대분류코드
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
C
267 
G
77 
F
28 
A
 
20
E
 
4
Other values (2)
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
C 267
66.8%
G 77
 
19.2%
F 28
 
7.0%
A 20
 
5.0%
E 4
 
1.0%
B 2
 
0.5%
D 2
 
0.5%

Length

2023-12-10T15:25:02.127679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:25:02.306147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 267
66.8%
g 77
 
19.2%
f 28
 
7.0%
a 20
 
5.0%
e 4
 
1.0%
b 2
 
0.5%
d 2
 
0.5%

표준산업업종상세분류코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27330.838
Minimum1110
Maximum46611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:25:02.603413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1110
5-th percentile7019.6
Q116297.25
median27205.5
Q341223.25
95-th percentile46462.05
Maximum46611
Range45501
Interquartile range (IQR)24926

Descriptive statistics

Standard deviation13314.104
Coefficient of variation (CV)0.48714583
Kurtosis-0.97281994
Mean27330.838
Median Absolute Deviation (MAD)11105
Skewness-0.050831793
Sum10932335
Variance1.7726535 × 108
MonotonicityStrictly increasing
2023-12-10T15:25:02.887901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1110 1
 
0.2%
32011 1
 
0.2%
33209 1
 
0.2%
33202 1
 
0.2%
33201 1
 
0.2%
33120 1
 
0.2%
33110 1
 
0.2%
32099 1
 
0.2%
32091 1
 
0.2%
32029 1
 
0.2%
Other values (390) 390
97.5%
ValueCountFrequency (%)
1110 1
0.2%
1121 1
0.2%
1122 1
0.2%
1123 1
0.2%
1131 1
0.2%
1132 1
0.2%
1140 1
0.2%
1152 1
0.2%
1159 1
0.2%
1212 1
0.2%
ValueCountFrequency (%)
46611 1
0.2%
46599 1
0.2%
46596 1
0.2%
46595 1
0.2%
46593 1
0.2%
46592 1
0.2%
46591 1
0.2%
46539 1
0.2%
46532 1
0.2%
46531 1
0.2%

표준산업업종상세분류명
Text

UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-10T15:25:03.380043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length13.875
Min length3

Characters and Unicode

Total characters5550
Distinct characters316
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)100.0%

Sample

1st row곡물 및 기타 식량작물 재배업
2nd row채소작물 재배업
3rd row화훼작물 재배업
4th row종자 및 묘목 생산업
5th row과실작물 재배업
ValueCountFrequency (%)
제조업 235
 
14.1%
및 193
 
11.6%
기타 97
 
5.8%
도매업 62
 
3.7%
외 28
 
1.7%
그 27
 
1.6%
공사업 16
 
1.0%
기기 16
 
1.0%
유사 14
 
0.8%
제품 13
 
0.8%
Other values (617) 967
58.0%
2023-12-10T15:25:04.126186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1268
22.8%
업 419
 
7.5%
제 312
 
5.6%
조 278
 
5.0%
기 216
 
3.9%
및 193
 
3.5%
품 121
 
2.2%
용 116
 
2.1%
타 103
 
1.9%
장 79
 
1.4%
Other values (306) 2445
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4277
77.1%
Space Separator 1268
 
22.8%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 419
 
9.8%
제 312
 
7.3%
조 278
 
6.5%
기 216
 
5.1%
및 193
 
4.5%
품 121
 
2.8%
용 116
 
2.7%
타 103
 
2.4%
장 79
 
1.8%
도 76
 
1.8%
Other values (302) 2364
55.3%
Space Separator
ValueCountFrequency (%)
1268
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4277
77.1%
Common 1273
 
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 419
 
9.8%
제 312
 
7.3%
조 278
 
6.5%
기 216
 
5.1%
및 193
 
4.5%
품 121
 
2.8%
용 116
 
2.7%
타 103
 
2.4%
장 79
 
1.8%
도 76
 
1.8%
Other values (302) 2364
55.3%
Common
ValueCountFrequency (%)
1268
99.6%
) 2
 
0.2%
( 2
 
0.2%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4258
76.7%
ASCII 1273
 
22.9%
Compat Jamo 19
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1268
99.6%
) 2
 
0.2%
( 2
 
0.2%
1 1
 
0.1%
Hangul
ValueCountFrequency (%)
업 419
 
9.8%
제 312
 
7.3%
조 278
 
6.5%
기 216
 
5.1%
및 193
 
4.5%
품 121
 
2.8%
용 116
 
2.7%
타 103
 
2.4%
장 79
 
1.9%
도 76
 
1.8%
Other values (301) 2345
55.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 19
100.0%

소상공인시스템로그일시
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2020-10-21 12:28:43
Maximum2020-10-21 12:28:43
2023-12-10T15:25:04.337061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:25:04.493613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-10T15:24:58.281904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:57.395675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:57.865201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:58.421543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:57.561898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:58.021578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:58.580963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:57.706290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:24:58.150449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:25:04.631864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제건수합계금액표준산업업종대분류코드표준산업업종상세분류코드
결제건수1.0001.0000.0000.000
합계금액1.0001.0000.0000.000
표준산업업종대분류코드0.0000.0001.0000.871
표준산업업종상세분류코드0.0000.0000.8711.000
2023-12-10T15:25:04.787080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제건수합계금액표준산업업종상세분류코드표준산업업종대분류코드
결제건수1.0000.9950.0780.000
합계금액0.9951.0000.0850.000
표준산업업종상세분류코드0.0780.0851.0000.689
표준산업업종대분류코드0.0000.0000.6891.000

Missing values

2023-12-10T15:24:58.828570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:24:59.188797image/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

소상공인결제분류코드년월소상공인시스템로그ID광역시도코드광역시도명결제건수합계금액표준산업업종대분류코드표준산업업종상세분류코드표준산업업종상세분류명소상공인시스템로그일시
0ZEROP41000202008<NA>41경기도113000A1110곡물 및 기타 식량작물 재배업2020-10-21 12:28:43.0
1ZEROP41000202008<NA>41경기도00A1121채소작물 재배업2020-10-21 12:28:43.0
2ZEROP41000202008<NA>41경기도00A1122화훼작물 재배업2020-10-21 12:28:43.0
3ZEROP41000202008<NA>41경기도00A1123종자 및 묘목 생산업2020-10-21 12:28:43.0
4ZEROP41000202008<NA>41경기도00A1131과실작물 재배업2020-10-21 12:28:43.0
5ZEROP41000202008<NA>41경기도00A1132음료용 및 향신용 작물 재배업2020-10-21 12:28:43.0
6ZEROP41000202008<NA>41경기도00A1140기타 작물 재배업2020-10-21 12:28:43.0
7ZEROP41000202008<NA>41경기도00A1152채소화훼 및 과실작물 시설 재배업2020-10-21 12:28:43.0
8ZEROP41000202008<NA>41경기도110000A1159기타 시설작물 재배업2020-10-21 12:28:43.0
9ZEROP41000202008<NA>41경기도00A1212육우 사육업2020-10-21 12:28:43.0
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