Overview

Dataset statistics

Number of variables9
Number of observations1538
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory115.8 KiB
Average record size in memory77.1 B

Variable types

Categorical2
Numeric4
Text3

Dataset

Description소득세법 제80조 제3항 단서 및 법인세법 제66조 제3항 단서에 따라 소득금액 추계결정 또는 경정을 하는 경우에 적용되는 경비율 및 업종코드 데이터 개방
URLhttps://www.data.go.kr/data/15036323/fileData.do

Alerts

귀속 has constant value ""Constant
업종코드 is highly overall correlated with 단순경비율(일반율) and 1 other fieldsHigh correlation
단순경비율(일반율) is highly overall correlated with 업종코드 and 1 other fieldsHigh correlation
기준경비율(일반율) is highly overall correlated with 단순경비율(일반율)High correlation
대분류 is highly overall correlated with 업종코드High correlation
업종코드 has unique valuesUnique
단순경비율(초과율) has 1499 (97.5%) zerosZeros

Reproduction

Analysis started2023-12-12 06:03:58.668578
Analysis finished2023-12-12 06:04:01.241494
Duration2.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

귀속
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2022
1538 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 1538
100.0%

Length

2023-12-12T15:04:01.313398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:04:01.421518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 1538
100.0%

업종코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1538
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean486791.36
Minimum11000
Maximum950002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-12T15:04:01.535221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile153101.85
Q1281101.25
median512294.5
Q3659903.75
95-th percentile924909.15
Maximum950002
Range939002
Interquartile range (IQR)378802.5

Descriptive statistics

Standard deviation244124.34
Coefficient of variation (CV)0.50149687
Kurtosis-0.83806735
Mean486791.36
Median Absolute Deviation (MAD)217709
Skewness0.25749488
Sum7.4868511 × 108
Variance5.9596695 × 1010
MonotonicityStrictly increasing
2023-12-12T15:04:01.714415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11000 1
 
0.1%
659905 1
 
0.1%
552103 1
 
0.1%
552102 1
 
0.1%
552101 1
 
0.1%
551017 1
 
0.1%
551016 1
 
0.1%
551015 1
 
0.1%
551010 1
 
0.1%
551009 1
 
0.1%
Other values (1528) 1528
99.3%
ValueCountFrequency (%)
11000 1
0.1%
11001 1
0.1%
11002 1
0.1%
11003 1
0.1%
11004 1
0.1%
11005 1
0.1%
11006 1
0.1%
11007 1
0.1%
11008 1
0.1%
11009 1
0.1%
ValueCountFrequency (%)
950002 1
0.1%
950001 1
0.1%
950000 1
0.1%
940929 1
0.1%
940928 1
0.1%
940927 1
0.1%
940926 1
0.1%
940925 1
0.1%
940924 1
0.1%
940923 1
0.1%

대분류
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
제조업
549 
도매 및 소매업
335 
협회 및 단체 수리 및 기타 개인서비스업
73 
운수 및 창고업
71 
전문 과학 및 기술서비스업
60 
Other values (14)
450 

Length

Max length33
Median length22
Mean length7.8771131
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row농업 임업 및 어업
2nd row농업 임업 및 어업
3rd row농업 임업 및 어업
4th row농업 임업 및 어업
5th row농업 임업 및 어업

Common Values

ValueCountFrequency (%)
제조업 549
35.7%
도매 및 소매업 335
21.8%
협회 및 단체 수리 및 기타 개인서비스업 73
 
4.7%
운수 및 창고업 71
 
4.6%
전문 과학 및 기술서비스업 60
 
3.9%
예술 스포츠 및 여가관련 서비스업 54
 
3.5%
건설업 52
 
3.4%
사업시설 관리 사업지원 및 임대 서비스업 46
 
3.0%
숙박 및 음식점업 43
 
2.8%
정보통신업 43
 
2.8%
Other values (9) 212
 
13.8%

Length

2023-12-12T15:04:01.898258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 888
22.7%
제조업 549
14.0%
도매 335
 
8.6%
소매업 335
 
8.6%
서비스업 130
 
3.3%
협회 73
 
1.9%
단체 73
 
1.9%
수리 73
 
1.9%
기타 73
 
1.9%
개인서비스업 73
 
1.9%
Other values (44) 1307
33.4%

중분류
Text

Distinct75
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T15:04:02.245352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length12.10013
Min length2

Characters and Unicode

Total characters18610
Distinct characters166
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row농업
2nd row농업
3rd row농업
4th row농업
5th row농업
ValueCountFrequency (%)
및 763
 
13.7%
제조업 537
 
9.7%
제외 296
 
5.3%
서비스업 223
 
4.0%
도매 177
 
3.2%
상품 177
 
3.2%
중개업 177
 
3.2%
자동차 173
 
3.1%
기타 145
 
2.6%
소매업 138
 
2.5%
Other values (145) 2757
49.6%
2023-12-12T15:04:02.749855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4025
21.6%
업 1532
 
8.2%
제 1121
 
6.0%
및 763
 
4.1%
품 606
 
3.3%
조 551
 
3.0%
비 414
 
2.2%
기 402
 
2.2%
매 344
 
1.8%
스 314
 
1.7%
Other values (156) 8538
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13975
75.1%
Space Separator 4025
 
21.6%
Other Punctuation 580
 
3.1%
Decimal Number 30
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1532
 
11.0%
제 1121
 
8.0%
및 763
 
5.5%
품 606
 
4.3%
조 551
 
3.9%
비 414
 
3.0%
기 402
 
2.9%
매 344
 
2.5%
스 314
 
2.2%
외 296
 
2.1%
Other values (152) 7632
54.6%
Other Punctuation
ValueCountFrequency (%)
; 296
51.0%
, 284
49.0%
Space Separator
ValueCountFrequency (%)
4025
100.0%
Decimal Number
ValueCountFrequency (%)
1 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13975
75.1%
Common 4635
 
24.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1532
 
11.0%
제 1121
 
8.0%
및 763
 
5.5%
품 606
 
4.3%
조 551
 
3.9%
비 414
 
3.0%
기 402
 
2.9%
매 344
 
2.5%
스 314
 
2.2%
외 296
 
2.1%
Other values (152) 7632
54.6%
Common
ValueCountFrequency (%)
4025
86.8%
; 296
 
6.4%
, 284
 
6.1%
1 30
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13964
75.0%
ASCII 4635
 
24.9%
Compat Jamo 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4025
86.8%
; 296
 
6.4%
, 284
 
6.1%
1 30
 
0.6%
Hangul
ValueCountFrequency (%)
업 1532
 
11.0%
제 1121
 
8.0%
및 763
 
5.5%
품 606
 
4.3%
조 551
 
3.9%
비 414
 
3.0%
기 402
 
2.9%
매 344
 
2.5%
스 314
 
2.2%
외 296
 
2.1%
Other values (151) 7621
54.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%

세분류
Text

Distinct476
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T15:04:03.063933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length28
Mean length13.598179
Min length2

Characters and Unicode

Total characters20914
Distinct characters332
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)9.8%

Sample

1st row곡물 및 기타 식량작물 재배업
2nd row채소 화훼작물 및 종묘 재배업
3rd row채소 화훼작물 및 종묘 재배업
4th row채소 화훼작물 및 종묘 재배업
5th row과실 음료용 및 향신용 작물 재배업
ValueCountFrequency (%)
및 724
 
11.4%
제조업 485
 
7.6%
기타 340
 
5.3%
도매업 164
 
2.6%
소매업 132
 
2.1%
서비스업 126
 
2.0%
외 110
 
1.7%
그 108
 
1.7%
의복 51
 
0.8%
운영업 50
 
0.8%
Other values (742) 4083
64.1%
2023-12-12T15:04:03.510936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4835
23.1%
업 1562
 
7.5%
제 785
 
3.8%
기 745
 
3.6%
및 730
 
3.5%
조 602
 
2.9%
품 514
 
2.5%
타 373
 
1.8%
매 325
 
1.6%
용 295
 
1.4%
Other values (322) 10148
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16057
76.8%
Space Separator 4835
 
23.1%
Decimal Number 17
 
0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1562
 
9.7%
제 785
 
4.9%
기 745
 
4.6%
및 730
 
4.5%
조 602
 
3.7%
품 514
 
3.2%
타 373
 
2.3%
매 325
 
2.0%
용 295
 
1.8%
물 284
 
1.8%
Other values (319) 9842
61.3%
Space Separator
ValueCountFrequency (%)
4835
100.0%
Decimal Number
ValueCountFrequency (%)
1 17
100.0%
Other Punctuation
ValueCountFrequency (%)
; 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16057
76.8%
Common 4857
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1562
 
9.7%
제 785
 
4.9%
기 745
 
4.6%
및 730
 
4.5%
조 602
 
3.7%
품 514
 
3.2%
타 373
 
2.3%
매 325
 
2.0%
용 295
 
1.8%
물 284
 
1.8%
Other values (319) 9842
61.3%
Common
ValueCountFrequency (%)
4835
99.5%
1 17
 
0.4%
; 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16009
76.5%
ASCII 4857
 
23.2%
Compat Jamo 48
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4835
99.5%
1 17
 
0.4%
; 5
 
0.1%
Hangul
ValueCountFrequency (%)
업 1562
 
9.8%
제 785
 
4.9%
기 745
 
4.7%
및 730
 
4.6%
조 602
 
3.8%
품 514
 
3.2%
타 373
 
2.3%
매 325
 
2.0%
용 295
 
1.8%
물 284
 
1.8%
Other values (318) 9794
61.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 48
100.0%

세세분류
Text

Distinct1201
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-12T15:04:03.870574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length107
Median length50
Mean length13.547464
Min length2

Characters and Unicode

Total characters20836
Distinct characters457
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1001 ?
Unique (%)65.1%

Sample

1st row곡물 및 기타 식량작물 재배업
2nd row채소작물 재배업
3rd row화훼작물 재배업
4th row종자 및 묘목 생산업
5th row과실작물 재배업
ValueCountFrequency (%)
및 655
 
10.4%
제조업 478
 
7.6%
기타 366
 
5.8%
도매업 164
 
2.6%
소매업 124
 
2.0%
외 120
 
1.9%
그 118
 
1.9%
서비스업 81
 
1.3%
운영업 62
 
1.0%
운송업 47
 
0.7%
Other values (1486) 4092
64.9%
2023-12-12T15:04:04.428637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4769
22.9%
업 1559
 
7.5%
제 726
 
3.5%
및 655
 
3.1%
기 655
 
3.1%
조 585
 
2.8%
타 385
 
1.8%
품 364
 
1.7%
매 336
 
1.6%
용 323
 
1.6%
Other values (447) 10479
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15986
76.7%
Space Separator 4769
 
22.9%
Open Punctuation 30
 
0.1%
Close Punctuation 30
 
0.1%
Decimal Number 17
 
0.1%
Uppercase Letter 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1559
 
9.8%
제 726
 
4.5%
및 655
 
4.1%
기 655
 
4.1%
조 585
 
3.7%
타 385
 
2.4%
품 364
 
2.3%
매 336
 
2.1%
용 323
 
2.0%
물 275
 
1.7%
Other values (440) 10123
63.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
4769
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Decimal Number
ValueCountFrequency (%)
1 17
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15986
76.7%
Common 4847
 
23.3%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1559
 
9.8%
제 726
 
4.5%
및 655
 
4.1%
기 655
 
4.1%
조 585
 
3.7%
타 385
 
2.4%
품 364
 
2.3%
매 336
 
2.1%
용 323
 
2.0%
물 275
 
1.7%
Other values (440) 10123
63.3%
Common
ValueCountFrequency (%)
4769
98.4%
( 30
 
0.6%
) 30
 
0.6%
1 17
 
0.4%
· 1
 
< 0.1%
Latin
ValueCountFrequency (%)
S 2
66.7%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15929
76.4%
ASCII 4849
 
23.3%
Compat Jamo 57
 
0.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4769
98.4%
( 30
 
0.6%
) 30
 
0.6%
1 17
 
0.4%
S 2
 
< 0.1%
N 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
업 1559
 
9.8%
제 726
 
4.6%
및 655
 
4.1%
기 655
 
4.1%
조 585
 
3.7%
타 385
 
2.4%
품 364
 
2.3%
매 336
 
2.1%
용 323
 
2.0%
물 275
 
1.7%
Other values (439) 10066
63.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 57
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

단순경비율(일반율)
Real number (ℝ)

HIGH CORRELATION 

Distinct299
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.023732
Minimum0
Maximum99.8
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-12T15:04:04.616628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile68.085
Q185.3
median90.2
Q392.4
95-th percentile95.5
Maximum99.8
Range99.8
Interquartile range (IQR)7.1

Descriptive statistics

Standard deviation10.163539
Coefficient of variation (CV)0.11679043
Kurtosis15.102605
Mean87.023732
Median Absolute Deviation (MAD)3.2
Skewness-3.204047
Sum133842.5
Variance103.29753
MonotonicityNot monotonic
2023-12-12T15:04:04.899285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89.6 47
 
3.1%
93.5 32
 
2.1%
90.6 30
 
2.0%
90.7 29
 
1.9%
91.2 29
 
1.9%
91.4 27
 
1.8%
91.6 26
 
1.7%
90.2 25
 
1.6%
93.7 24
 
1.6%
91.5 24
 
1.6%
Other values (289) 1245
80.9%
ValueCountFrequency (%)
0.0 2
0.1%
14.6 1
0.1%
22.3 1
0.1%
25.7 1
0.1%
29.0 1
0.1%
35.4 2
0.1%
36.9 1
0.1%
37.4 1
0.1%
40.9 1
0.1%
41.5 1
0.1%
ValueCountFrequency (%)
99.8 1
 
0.1%
99.6 1
 
0.1%
98.9 1
 
0.1%
98.3 2
 
0.1%
98.2 1
 
0.1%
97.7 1
 
0.1%
97.5 5
0.3%
97.4 1
 
0.1%
97.3 3
0.2%
97.2 5
0.3%

단순경비율(초과율)
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3345904
Minimum0
Maximum74.5
Zeros1499
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-12T15:04:05.032255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum74.5
Range74.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.6329942
Coefficient of variation (CV)6.4686471
Kurtosis42.979501
Mean1.3345904
Median Absolute Deviation (MAD)0
Skewness6.5978403
Sum2052.6
Variance74.528588
MonotonicityNot monotonic
2023-12-12T15:04:05.173593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 1499
97.5%
49.7 5
 
0.3%
65.0 5
 
0.3%
54.2 3
 
0.2%
46.4 2
 
0.1%
72.0 1
 
0.1%
56.5 1
 
0.1%
58.0 1
 
0.1%
55.9 1
 
0.1%
71.2 1
 
0.1%
Other values (19) 19
 
1.2%
ValueCountFrequency (%)
0.0 1499
97.5%
6.9 1
 
0.1%
10.4 1
 
0.1%
24.3 1
 
0.1%
29.6 1
 
0.1%
34.3 1
 
0.1%
36.3 1
 
0.1%
41.8 1
 
0.1%
42.2 1
 
0.1%
46.4 2
 
0.1%
ValueCountFrequency (%)
74.5 1
 
0.1%
72.3 1
 
0.1%
72.0 1
 
0.1%
71.2 1
 
0.1%
68.6 1
 
0.1%
66.4 1
 
0.1%
65.0 5
0.3%
63.2 1
 
0.1%
60.1 1
 
0.1%
59.3 1
 
0.1%

기준경비율(일반율)
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.908388
Minimum0
Maximum39.9
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-12T15:04:05.337683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q17.725
median11.8
Q317.5
95-th percentile25.615
Maximum39.9
Range39.9
Interquartile range (IQR)9.775

Descriptive statistics

Standard deviation6.9830365
Coefficient of variation (CV)0.54096892
Kurtosis-0.13457011
Mean12.908388
Median Absolute Deviation (MAD)5
Skewness0.59939139
Sum19853.1
Variance48.762799
MonotonicityNot monotonic
2023-12-12T15:04:05.524298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.2 24
 
1.6%
12.4 24
 
1.6%
17.4 19
 
1.2%
12.8 19
 
1.2%
11.0 17
 
1.1%
6.1 16
 
1.0%
12.0 16
 
1.0%
8.6 16
 
1.0%
10.5 16
 
1.0%
11.2 15
 
1.0%
Other values (273) 1356
88.2%
ValueCountFrequency (%)
0.0 2
0.1%
0.8 1
 
0.1%
0.9 2
0.1%
1.1 1
 
0.1%
1.5 3
0.2%
1.6 2
0.1%
1.7 2
0.1%
1.8 2
0.1%
1.9 4
0.3%
2.0 1
 
0.1%
ValueCountFrequency (%)
39.9 3
0.2%
35.4 1
 
0.1%
34.7 1
 
0.1%
33.4 1
 
0.1%
32.2 1
 
0.1%
31.3 2
0.1%
31.0 1
 
0.1%
30.8 1
 
0.1%
30.4 2
0.1%
30.2 1
 
0.1%

Interactions

2023-12-12T15:04:00.557796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.400141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.793082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.187846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.653129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.490260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.882182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.280231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.747232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.589291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.968801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.365266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.842441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:03:59.683271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.071260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:04:00.456055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:04:05.670172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드대분류중분류단순경비율(일반율)단순경비율(초과율)기준경비율(일반율)
업종코드1.0000.9670.9980.6590.3090.770
대분류0.9671.0001.0000.6750.5140.742
중분류0.9981.0001.0000.7540.6340.835
단순경비율(일반율)0.6590.6750.7541.0000.6470.504
단순경비율(초과율)0.3090.5140.6340.6471.0000.191
기준경비율(일반율)0.7700.7420.8350.5040.1911.000
2023-12-12T15:04:06.115213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드단순경비율(일반율)단순경비율(초과율)기준경비율(일반율)대분류
업종코드1.000-0.6200.2710.3780.825
단순경비율(일반율)-0.6201.000-0.246-0.5030.327
단순경비율(초과율)0.271-0.2461.0000.1410.228
기준경비율(일반율)0.378-0.5030.1411.0000.388
대분류0.8250.3270.2280.3881.000

Missing values

2023-12-12T15:04:01.008499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:04:01.171981image/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

귀속업종코드대분류중분류세분류세세분류단순경비율(일반율)단순경비율(초과율)기준경비율(일반율)
0202211000농업 임업 및 어업농업곡물 및 기타 식량작물 재배업곡물 및 기타 식량작물 재배업0.00.00.0
1202211001농업 임업 및 어업농업채소 화훼작물 및 종묘 재배업채소작물 재배업93.50.08.1
2202211002농업 임업 및 어업농업채소 화훼작물 및 종묘 재배업화훼작물 재배업93.50.06.0
3202211003농업 임업 및 어업농업채소 화훼작물 및 종묘 재배업종자 및 묘목 생산업93.50.08.2
4202211004농업 임업 및 어업농업과실 음료용 및 향신용 작물 재배업과실작물 재배업93.50.04.5
5202211005농업 임업 및 어업농업과실 음료용 및 향신용 작물 재배업음료용 및 향신용 작물 재배업93.50.09.0
6202211006농업 임업 및 어업농업기타 작물 재배업기타 작물 재배업93.50.08.6
7202211007농업 임업 및 어업농업시설작물 재배업콩나물 재배업93.50.06.3
8202211008농업 임업 및 어업농업시설작물 재배업채소 화훼 및 과실작물 시설 재배업93.50.08.6
9202211009농업 임업 및 어업농업시설작물 재배업기타 시설작물 재배업93.50.08.2
귀속업종코드대분류중분류세분류세세분류단순경비율(일반율)단순경비율(초과율)기준경비율(일반율)
15282022940923협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업대출모집인67.354.227.5
15292022940924협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업신용카드회원 모집인70.058.028.4
15302022940925협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업방과후강사68.956.516.5
15312022940926협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업소프트웨어프리랜서64.149.717.0
15322022940927협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업관광통역안내사64.149.717.0
15332022940928협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업어린이통학버스기사64.149.717.0
15342022940929협회 및 단체 수리 및 기타 개인서비스업인적용역기타자영업중고자동차판매원75.065.022.0
15352022950000협회 및 단체 수리 및 기타 개인서비스업기타 개인 서비스업그 외 기타 분류 안된 개인 서비스업그 외 기타 달리 분류되지 않은 개인 서비스업84.30.017.0
15362022950001가구 내 고용활동 및 달리 분류되지 않은 자가 소비 생산활동가구 내 고용활동가구 내 고용활동가구 내 고용활동79.70.018.2
15372022950002보건업 및 사회복지 서비스업사회복지 서비스업보육시설 운영업보육시설 운영업86.60.013.0