Overview

Dataset statistics

Number of variables9
Number of observations194
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory76.7 B

Variable types

Numeric4
Categorical3
Text2

Dataset

Description2015년 제·개정된 농축수산물 표준코드의 도매시장 법인과 동일한 의미를 가지는 과거에 사용하던 도매시장 법인코드를 나타낸 정보
Author농림수산식품교육문화정보원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20191011000000001244

Alerts

업데이트일자 (updtDe) has constant value ""Constant
구시장명 (marketOldNm) is highly overall correlated with 시장코드 (whsalMrktCode) and 4 other fieldsHigh correlation
시장명 (whsalMrktNm) is highly overall correlated with 시장코드 (whsalMrktCode) and 4 other fieldsHigh correlation
시장코드 (whsalMrktCode) is highly overall correlated with 구시장코드 (whsalOldCode) and 4 other fieldsHigh correlation
구시장코드 (whsalOldCode) is highly overall correlated with 시장코드 (whsalMrktCode) and 4 other fieldsHigh correlation
법인코드 (cprCode) is highly overall correlated with 시장코드 (whsalMrktCode) and 4 other fieldsHigh correlation
구법인코드 (cprOldCode) is highly overall correlated with 시장코드 (whsalMrktCode) and 4 other fieldsHigh correlation
법인코드 (cprCode) has unique valuesUnique
구법인코드 (cprOldCode) has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:53:24.025005
Analysis finished2023-12-11 03:53:26.889109
Duration2.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시장코드 (whsalMrktCode)
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1104113.9
Minimum1005601
Maximum3054001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T12:53:27.016884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1005601
5-th percentile1005601
Q11007701
median1024201
Q31046901
95-th percentile2017716
Maximum3054001
Range2048400
Interquartile range (IQR)39200

Descriptive statistics

Standard deviation324062.73
Coefficient of variation (CV)0.29350481
Kurtosis20.776472
Mean1104113.9
Median Absolute Deviation (MAD)16500
Skewness4.4676756
Sum2.141981 × 108
Variance1.0501666 × 1011
MonotonicityNot monotonic
2023-12-11T12:53:27.166421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1007701 55
28.4%
1005601 11
 
5.7%
1041401 10
 
5.2%
1011901 7
 
3.6%
1015201 6
 
3.1%
1034301 5
 
2.6%
1046901 5
 
2.6%
1048001 5
 
2.6%
1044701 5
 
2.6%
1013901 5
 
2.6%
Other values (35) 80
41.2%
ValueCountFrequency (%)
1005601 11
 
5.7%
1007701 55
28.4%
1011901 7
 
3.6%
1013901 5
 
2.6%
1015201 6
 
3.1%
1016301 5
 
2.6%
1021401 3
 
1.5%
1021501 4
 
2.1%
1024201 3
 
1.5%
1025401 1
 
0.5%
ValueCountFrequency (%)
3054001 1
0.5%
3039601 1
0.5%
3033001 1
0.5%
2059601 1
0.5%
2058701 1
0.5%
2041901 1
0.5%
2039601 1
0.5%
2038901 1
0.5%
2038101 1
0.5%
2037801 1
0.5%

시장명 (whsalMrktNm)
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
강서농수산물도매시장
55 
가락동농수산물시장
11 
대구북부도매시장
 
10
구리농수산물도매시장
 
7
안산농수산물도매시장
 
6
Other values (40)
105 

Length

Max length12
Median length10
Mean length9.9536082
Min length6

Unique

Unique13 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
강서농수산물도매시장 55
28.4%
가락동농수산물시장 11
 
5.7%
대구북부도매시장 10
 
5.2%
구리농수산물도매시장 7
 
3.6%
안산농수산물도매시장 6
 
3.1%
울산농수산물도매시장 5
 
2.6%
안양농수산물도매시장 5
 
2.6%
수원농수산물도매시장 5
 
2.6%
부산반여농산물도매시장 5
 
2.6%
부산엄궁농산물도매시장 5
 
2.6%
Other values (35) 80
41.2%

Length

2023-12-11T12:53:27.357197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서농수산물도매시장 55
28.4%
가락동농수산물시장 11
 
5.7%
대구북부도매시장 10
 
5.2%
구리농수산물도매시장 7
 
3.6%
안산농수산물도매시장 6
 
3.1%
부산반여농산물도매시장 5
 
2.6%
부산엄궁농산물도매시장 5
 
2.6%
대전오정농수산물도매시장 5
 
2.6%
수원농수산물도매시장 5
 
2.6%
안양농수산물도매시장 5
 
2.6%
Other values (35) 80
41.2%

구시장코드 (whsalOldCode)
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean232429.78
Minimum110001
Maximum380401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T12:53:27.512851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110001
5-th percentile110001
Q1110008
median230002
Q3327651
95-th percentile380136
Maximum380401
Range270400
Interquartile range (IQR)217643

Descriptive statistics

Standard deviation102632.87
Coefficient of variation (CV)0.44156505
Kurtosis-1.5572663
Mean232429.78
Median Absolute Deviation (MAD)119994
Skewness-0.010224896
Sum45091378
Variance1.0533506 × 1010
MonotonicityIncreasing
2023-12-11T12:53:27.732337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
110008 55
28.4%
110001 11
 
5.7%
220001 10
 
5.2%
311201 7
 
3.6%
310901 6
 
3.1%
250001 5
 
2.6%
210001 5
 
2.6%
210009 5
 
2.6%
380201 5
 
2.6%
310401 5
 
2.6%
Other values (35) 80
41.2%
ValueCountFrequency (%)
110001 11
 
5.7%
110003 1
 
0.5%
110005 1
 
0.5%
110008 55
28.4%
210001 5
 
2.6%
210005 4
 
2.1%
210009 5
 
2.6%
220001 10
 
5.2%
220003 1
 
0.5%
230001 4
 
2.1%
ValueCountFrequency (%)
380401 2
 
1.0%
380303 3
1.5%
380201 5
2.6%
380101 2
 
1.0%
371501 2
 
1.0%
370701 1
 
0.5%
370401 2
 
1.0%
370301 1
 
0.5%
370203 1
 
0.5%
370201 1
 
0.5%

구시장명 (marketOldNm)
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
서울강서도매시장
55 
서울가락도매시장
11 
대구북부도매시장
 
10
구리도매시장
 
7
안산도매시장
 
6
Other values (40)
105 

Length

Max length11
Median length8
Mean length7.2886598
Min length6

Unique

Unique13 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
서울강서도매시장 55
28.4%
서울가락도매시장 11
 
5.7%
대구북부도매시장 10
 
5.2%
구리도매시장 7
 
3.6%
안산도매시장 6
 
3.1%
울산도매시장 5
 
2.6%
안양도매시장 5
 
2.6%
수원도매시장 5
 
2.6%
부산반여도매시장 5
 
2.6%
부산엄궁도매시장 5
 
2.6%
Other values (35) 80
41.2%

Length

2023-12-11T12:53:27.866946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울강서도매시장 55
28.4%
서울가락도매시장 11
 
5.7%
대구북부도매시장 10
 
5.2%
구리도매시장 7
 
3.6%
안산도매시장 6
 
3.1%
부산반여도매시장 5
 
2.6%
부산엄궁도매시장 5
 
2.6%
대전오정도매시장 5
 
2.6%
수원도매시장 5
 
2.6%
안양도매시장 5
 
2.6%
Other values (35) 80
41.2%

법인코드 (cprCode)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct194
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6026804.3
Minimum6005601
Maximum6061905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T12:53:28.015449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6005601
5-th percentile6005612.7
Q16007736.2
median6021504.5
Q36044001.2
95-th percentile6058184
Maximum6061905
Range56304
Interquartile range (IQR)36265

Descriptive statistics

Standard deviation18902.127
Coefficient of variation (CV)0.0031363432
Kurtosis-1.3668216
Mean6026804.3
Median Absolute Deviation (MAD)13792
Skewness0.37861037
Sum1.1692 × 109
Variance3.5729039 × 108
MonotonicityNot monotonic
2023-12-11T12:53:28.184820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6005601 1
 
0.5%
6028705 1
 
0.5%
6013901 1
 
0.5%
6013902 1
 
0.5%
6015202 1
 
0.5%
6015201 1
 
0.5%
6015206 1
 
0.5%
6015205 1
 
0.5%
6015204 1
 
0.5%
6015203 1
 
0.5%
Other values (184) 184
94.8%
ValueCountFrequency (%)
6005601 1
0.5%
6005603 1
0.5%
6005604 1
0.5%
6005605 1
0.5%
6005606 1
0.5%
6005607 1
0.5%
6005609 1
0.5%
6005610 1
0.5%
6005611 1
0.5%
6005612 1
0.5%
ValueCountFrequency (%)
6061905 1
0.5%
6061904 1
0.5%
6061903 1
0.5%
6061902 1
0.5%
6061105 1
0.5%
6061103 1
0.5%
6061102 1
0.5%
6061101 1
0.5%
6059601 1
0.5%
6058702 1
0.5%

법인명 (cprNM)
Text

Distinct188
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-11T12:53:28.484920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.3041237
Min length4

Characters and Unicode

Total characters1029
Distinct characters148
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)93.8%

Sample

1st row서울청과
2nd row농협가락(공)
3rd row중앙청과
4th row동부팜청과
5th row한국청과
ValueCountFrequency (%)
양념류조합 2
 
1.0%
상장예외(수산 2
 
1.0%
상장예외(청과 2
 
1.0%
무배추조합 2
 
1.0%
중원청과 2
 
1.0%
호남청과 2
 
1.0%
서울청과 1
 
0.5%
고려청과 1
 
0.5%
안양평촌(주 1
 
0.5%
주)안양청과 1
 
0.5%
Other values (178) 178
91.8%
2023-12-11T12:53:28.992274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 82
 
8.0%
과 79
 
7.7%
산 68
 
6.6%
( 53
 
5.2%
) 53
 
5.2%
협 44
 
4.3%
농 43
 
4.2%
공 43
 
4.2%
수 35
 
3.4%
원 31
 
3.0%
Other values (138) 498
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 915
88.9%
Open Punctuation 53
 
5.2%
Close Punctuation 53
 
5.2%
Uppercase Letter 6
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
Uppercase Letter
ValueCountFrequency (%)
V 2
33.3%
F 2
33.3%
W 1
16.7%
P 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 915
88.9%
Common 108
 
10.5%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
Latin
ValueCountFrequency (%)
V 2
33.3%
F 2
33.3%
W 1
16.7%
P 1
16.7%
Common
ValueCountFrequency (%)
( 53
49.1%
) 53
49.1%
& 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 915
88.9%
ASCII 114
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
ASCII
ValueCountFrequency (%)
( 53
46.5%
) 53
46.5%
V 2
 
1.8%
& 2
 
1.8%
F 2
 
1.8%
W 1
 
0.9%
P 1
 
0.9%

구법인코드 (cprOldCode)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct194
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23242996
Minimum11000101
Maximum38040102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T12:53:29.197510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000101
5-th percentile11000163
Q111000853
median23000202
Q332765101
95-th percentile38013602
Maximum38040102
Range27040001
Interquartile range (IQR)21764248

Descriptive statistics

Standard deviation10263273
Coefficient of variation (CV)0.44156412
Kurtosis-1.5572665
Mean23242996
Median Absolute Deviation (MAD)11999340
Skewness-0.010223935
Sum4.5091412 × 109
Variance1.0533477 × 1014
MonotonicityStrictly increasing
2023-12-11T12:53:29.382186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11000101 1
 
0.5%
33010102 1
 
0.5%
31040104 1
 
0.5%
31040192 1
 
0.5%
31090101 1
 
0.5%
31090102 1
 
0.5%
31090103 1
 
0.5%
31090104 1
 
0.5%
31090105 1
 
0.5%
31090192 1
 
0.5%
Other values (184) 184
94.8%
ValueCountFrequency (%)
11000101 1
0.5%
11000102 1
0.5%
11000103 1
0.5%
11000104 1
0.5%
11000105 1
0.5%
11000106 1
0.5%
11000107 1
0.5%
11000108 1
0.5%
11000109 1
0.5%
11000110 1
0.5%
ValueCountFrequency (%)
38040102 1
0.5%
38040101 1
0.5%
38030303 1
0.5%
38030302 1
0.5%
38030301 1
0.5%
38020105 1
0.5%
38020104 1
0.5%
38020103 1
0.5%
38020102 1
0.5%
38020101 1
0.5%

구법인명 (cprOldNM)
Text

Distinct188
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-11T12:53:29.705040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.3041237
Min length4

Characters and Unicode

Total characters1029
Distinct characters148
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)93.8%

Sample

1st row서울청과
2nd row농협가락(공)
3rd row중앙청과
4th row동부팜청과
5th row한국청과
ValueCountFrequency (%)
양념류조합 2
 
1.0%
상장예외(수산 2
 
1.0%
상장예외(청과 2
 
1.0%
무배추조합 2
 
1.0%
중원청과 2
 
1.0%
호남청과 2
 
1.0%
서울청과 1
 
0.5%
고려청과 1
 
0.5%
안양평촌(주 1
 
0.5%
주)안양청과 1
 
0.5%
Other values (178) 178
91.8%
2023-12-11T12:53:30.162123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 82
 
8.0%
과 79
 
7.7%
산 68
 
6.6%
( 53
 
5.2%
) 53
 
5.2%
협 44
 
4.3%
농 43
 
4.2%
공 43
 
4.2%
수 35
 
3.4%
원 31
 
3.0%
Other values (138) 498
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 915
88.9%
Open Punctuation 53
 
5.2%
Close Punctuation 53
 
5.2%
Uppercase Letter 6
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
Uppercase Letter
ValueCountFrequency (%)
V 2
33.3%
F 2
33.3%
W 1
16.7%
P 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 915
88.9%
Common 108
 
10.5%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
Latin
ValueCountFrequency (%)
V 2
33.3%
F 2
33.3%
W 1
16.7%
P 1
16.7%
Common
ValueCountFrequency (%)
( 53
49.1%
) 53
49.1%
& 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 915
88.9%
ASCII 114
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 82
 
9.0%
과 79
 
8.6%
산 68
 
7.4%
협 44
 
4.8%
농 43
 
4.7%
공 43
 
4.7%
수 35
 
3.8%
원 31
 
3.4%
주 25
 
2.7%
대 21
 
2.3%
Other values (131) 444
48.5%
ASCII
ValueCountFrequency (%)
( 53
46.5%
) 53
46.5%
V 2
 
1.8%
& 2
 
1.8%
F 2
 
1.8%
W 1
 
0.9%
P 1
 
0.9%

업데이트일자 (updtDe)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2015-12-15
194 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-12-15
2nd row2015-12-15
3rd row2015-12-15
4th row2015-12-15
5th row2015-12-15

Common Values

ValueCountFrequency (%)
2015-12-15 194
100.0%

Length

2023-12-11T12:53:30.330895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:53:30.432446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-12-15 194
100.0%

Interactions

2023-12-11T12:53:25.804166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:24.503034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:24.905497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.363952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.908520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:24.597260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.012121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.466160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:26.019782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:24.716174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.129843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.570433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:26.136718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:24.812463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.272666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:53:25.699422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:53:30.497245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장코드 (whsalMrktCode)시장명 (whsalMrktNm)구시장코드 (whsalOldCode)구시장명 (marketOldNm)법인코드 (cprCode)구법인코드 (cprOldCode)
시장코드 (whsalMrktCode)1.0001.0000.3121.0000.2380.312
시장명 (whsalMrktNm)1.0001.0001.0001.0001.0001.000
구시장코드 (whsalOldCode)0.3121.0001.0001.0000.9351.000
구시장명 (marketOldNm)1.0001.0001.0001.0001.0001.000
법인코드 (cprCode)0.2381.0000.9351.0001.0000.935
구법인코드 (cprOldCode)0.3121.0001.0001.0000.9351.000
2023-12-11T12:53:30.619574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구시장명 (marketOldNm)시장명 (whsalMrktNm)
구시장명 (marketOldNm)1.0001.000
시장명 (whsalMrktNm)1.0001.000
2023-12-11T12:53:30.715639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장코드 (whsalMrktCode)구시장코드 (whsalOldCode)법인코드 (cprCode)구법인코드 (cprOldCode)시장명 (whsalMrktNm)구시장명 (marketOldNm)
시장코드 (whsalMrktCode)1.0000.7150.9140.7070.8860.886
구시장코드 (whsalOldCode)0.7151.0000.7310.9880.8930.893
법인코드 (cprCode)0.9140.7311.0000.7230.9000.900
구법인코드 (cprOldCode)0.7070.9880.7231.0000.8930.893
시장명 (whsalMrktNm)0.8860.8930.9000.8931.0001.000
구시장명 (marketOldNm)0.8860.8930.9000.8931.0001.000

Missing values

2023-12-11T12:53:26.528170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:53:26.795768image/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

시장코드 (whsalMrktCode)시장명 (whsalMrktNm)구시장코드 (whsalOldCode)구시장명 (marketOldNm)법인코드 (cprCode)법인명 (cprNM)구법인코드 (cprOldCode)구법인명 (cprOldNM)업데이트일자 (updtDe)
01005601가락동농수산물시장110001서울가락도매시장6005601서울청과11000101서울청과2015-12-15
11005601가락동농수산물시장110001서울가락도매시장6005607농협가락(공)11000102농협가락(공)2015-12-15
21005601가락동농수산물시장110001서울가락도매시장6005604중앙청과11000103중앙청과2015-12-15
31005601가락동농수산물시장110001서울가락도매시장6005610동부팜청과11000104동부팜청과2015-12-15
41005601가락동농수산물시장110001서울가락도매시장6005605한국청과11000105한국청과2015-12-15
51005601가락동농수산물시장110001서울가락도매시장6005609대아청과11000106대아청과2015-12-15
61005601가락동농수산물시장110001서울가락도매시장6005606강동수산11000107강동수산2015-12-15
71005601가락동농수산물시장110001서울가락도매시장6005613서울수협(공)11000108서울수협(공)2015-12-15
81005601가락동농수산물시장110001서울가락도매시장6005612서울건해11000109서울건해2015-12-15
91005601가락동농수산물시장110001서울가락도매시장6005603서울축협(공)11000110서울축협(공)2015-12-15
시장코드 (whsalMrktCode)시장명 (whsalMrktNm)구시장코드 (whsalOldCode)구시장명 (marketOldNm)법인코드 (cprCode)법인명 (cprNM)구법인코드 (cprOldCode)구법인명 (cprOldNM)업데이트일자 (updtDe)
1841044701울산농수산물도매시장380201울산도매시장6044703울산원협(공)38020101울산원협(공)2015-12-15
1851044701울산농수산물도매시장380201울산도매시장6044705울산중앙청과38020102울산중앙청과2015-12-15
1861044701울산농수산물도매시장380201울산도매시장6044702울산수협(공)38020103울산수협(공)2015-12-15
1871044701울산농수산물도매시장380201울산도매시장6044704울산중앙수산38020104울산중앙수산2015-12-15
1881044701울산농수산물도매시장380201울산도매시장6044701울산건해38020105울산건해2015-12-15
1891051101창원내서농산물도매시장380303창원내서도매시장6051114마산청과38030301마산청과2015-12-15
1901051101창원내서농산물도매시장380303창원내서도매시장6051113창원원협(공)38030302창원원협(공)2015-12-15
1911051101창원내서농산물도매시장380303창원내서도매시장6051101중부화훼농협(공)38030303중부화훼농협(공)2015-12-15
1921052601진주농산물도매시장380401진주도매시장6052611진주원협(공)38040101진주원협(공)2015-12-15
1931052601진주농산물도매시장380401진주도매시장6052601진주중앙청과38040102진주중앙청과2015-12-15