Overview

Dataset statistics

Number of variables4
Number of observations208
Missing cells591
Missing cells (%)71.0%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory6.8 KiB
Average record size in memory33.6 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description인천광역시 부평구 축산물 수입 판매업 데이터입니다.(판매업구분명,사업장명칭,소재지주소(도로명),소재지전화)ex) 축산물수입판매업,동서식품(주),인천광역시 부평구 부평북로 215 (청천동),500-3228
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089259&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (0.5%) duplicate rowsDuplicates
연번 is highly overall correlated with 판매업구분명High correlation
판매업구분명 is highly overall correlated with 연번High correlation
판매업구분명 is highly imbalanced (70.1%)Imbalance
연번 has 197 (94.7%) missing valuesMissing
사업장명칭 has 197 (94.7%) missing valuesMissing
소재지주소(도로명) has 197 (94.7%) missing valuesMissing

Reproduction

Analysis started2024-01-28 06:35:00.965489
Analysis finished2024-01-28 06:35:01.555862
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing197
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean6
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-01-28T15:35:01.595154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.5
Q13.5
median6
Q38.5
95-th percentile10.5
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.3166248
Coefficient of variation (CV)0.5527708
Kurtosis-1.2
Mean6
Median Absolute Deviation (MAD)3
Skewness0
Sum66
Variance11
MonotonicityStrictly increasing
2024-01-28T15:35:01.672426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 1
 
0.5%
2 1
 
0.5%
3 1
 
0.5%
4 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
8 1
 
0.5%
9 1
 
0.5%
10 1
 
0.5%
(Missing) 197
94.7%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
11 1
0.5%
10 1
0.5%
9 1
0.5%
8 1
0.5%
7 1
0.5%
6 1
0.5%
5 1
0.5%
4 1
0.5%
3 1
0.5%
2 1
0.5%

판매업구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
197 
축산물수입판매업
 
11

Length

Max length8
Median length4
Mean length4.2115385
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 197
94.7%
축산물수입판매업 11
 
5.3%

Length

2024-01-28T15:35:01.768923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:35:01.856107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
94.7%
축산물수입판매업 11
 
5.3%

사업장명칭
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing197
Missing (%)94.7%
Memory size1.8 KiB
2024-01-28T15:35:01.999455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.3636364
Min length4

Characters and Unicode

Total characters81
Distinct characters47
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

Unique11 ?
Unique (%)100.0%

Sample

1st row(주)새한 에프앤비
2nd row(주)영광축산유통
3rd row(주)하나로 미트
4th rowJ & P 통상
5th row동서식품(주)
ValueCountFrequency (%)
주)새한 1
 
5.6%
에프앤비 1
 
5.6%
중부미트넷(주 1
 
5.6%
유로미트 1
 
5.6%
오킴스트레이딩 1
 
5.6%
무역 1
 
5.6%
세이오 1
 
5.6%
주식회사 1
 
5.6%
삼지무역 1
 
5.6%
동서식품(주 1
 
5.6%
Other values (8) 8
44.4%
2024-01-28T15:35:02.254047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
8.6%
주 6
 
7.4%
( 5
 
6.2%
) 5
 
6.2%
트 5
 
6.2%
미 4
 
4.9%
오 2
 
2.5%
무 2
 
2.5%
역 2
 
2.5%
로 2
 
2.5%
Other values (37) 41
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
75.3%
Space Separator 7
 
8.6%
Open Punctuation 5
 
6.2%
Close Punctuation 5
 
6.2%
Uppercase Letter 2
 
2.5%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6
 
9.8%
트 5
 
8.2%
미 4
 
6.6%
오 2
 
3.3%
무 2
 
3.3%
역 2
 
3.3%
로 2
 
3.3%
통 2
 
3.3%
이 2
 
3.3%
유 2
 
3.3%
Other values (31) 32
52.5%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
75.3%
Common 18
 
22.2%
Latin 2
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6
 
9.8%
트 5
 
8.2%
미 4
 
6.6%
오 2
 
3.3%
무 2
 
3.3%
역 2
 
3.3%
로 2
 
3.3%
통 2
 
3.3%
이 2
 
3.3%
유 2
 
3.3%
Other values (31) 32
52.5%
Common
ValueCountFrequency (%)
7
38.9%
( 5
27.8%
) 5
27.8%
& 1
 
5.6%
Latin
ValueCountFrequency (%)
P 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
75.3%
ASCII 20
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
35.0%
( 5
25.0%
) 5
25.0%
P 1
 
5.0%
J 1
 
5.0%
& 1
 
5.0%
Hangul
ValueCountFrequency (%)
주 6
 
9.8%
트 5
 
8.2%
미 4
 
6.6%
오 2
 
3.3%
무 2
 
3.3%
역 2
 
3.3%
로 2
 
3.3%
통 2
 
3.3%
이 2
 
3.3%
유 2
 
3.3%
Other values (31) 32
52.5%

소재지주소(도로명)
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing197
Missing (%)94.7%
Memory size1.8 KiB
2024-01-28T15:35:02.418219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length29.818182
Min length23

Characters and Unicode

Total characters328
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평대로 163 (부평동)
2nd row인천광역시 부평구 열우물로 18 (십정동, 동암역 대우 마이빌)
3rd row인천광역시 부평구 열우물로 18, 809호 (십정동,대우마이빌 오피스텔)
4th row인천광역시 부평구 동암광장로8번길 8 (십정동)
5th row인천광역시 부평구 부평북로 215 (청천동)
ValueCountFrequency (%)
인천광역시 11
17.5%
부평구 11
17.5%
부평동 4
 
6.3%
청천동 3
 
4.8%
열우물로 2
 
3.2%
18 2
 
3.2%
십정동 2
 
3.2%
장제로 1
 
1.6%
36 1
 
1.6%
갈산동 1
 
1.6%
Other values (25) 25
39.7%
2024-01-28T15:35:02.673566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
15.9%
부 19
 
5.8%
평 18
 
5.5%
천 15
 
4.6%
동 13
 
4.0%
광 12
 
3.7%
역 12
 
3.7%
인 11
 
3.4%
) 11
 
3.4%
시 11
 
3.4%
Other values (51) 154
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
61.9%
Space Separator 52
 
15.9%
Decimal Number 43
 
13.1%
Close Punctuation 11
 
3.4%
Open Punctuation 11
 
3.4%
Other Punctuation 6
 
1.8%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 19
 
9.4%
평 18
 
8.9%
천 15
 
7.4%
동 13
 
6.4%
광 12
 
5.9%
역 12
 
5.9%
인 11
 
5.4%
시 11
 
5.4%
구 11
 
5.4%
로 11
 
5.4%
Other values (36) 70
34.5%
Decimal Number
ValueCountFrequency (%)
1 10
23.3%
6 6
14.0%
8 5
11.6%
4 5
11.6%
2 4
 
9.3%
0 4
 
9.3%
5 3
 
7.0%
3 3
 
7.0%
7 2
 
4.7%
9 1
 
2.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
61.9%
Common 125
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 19
 
9.4%
평 18
 
8.9%
천 15
 
7.4%
동 13
 
6.4%
광 12
 
5.9%
역 12
 
5.9%
인 11
 
5.4%
시 11
 
5.4%
구 11
 
5.4%
로 11
 
5.4%
Other values (36) 70
34.5%
Common
ValueCountFrequency (%)
52
41.6%
) 11
 
8.8%
( 11
 
8.8%
1 10
 
8.0%
, 6
 
4.8%
6 6
 
4.8%
8 5
 
4.0%
4 5
 
4.0%
2 4
 
3.2%
0 4
 
3.2%
Other values (5) 11
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
61.9%
ASCII 125
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
41.6%
) 11
 
8.8%
( 11
 
8.8%
1 10
 
8.0%
, 6
 
4.8%
6 6
 
4.8%
8 5
 
4.0%
4 5
 
4.0%
2 4
 
3.2%
0 4
 
3.2%
Other values (5) 11
 
8.8%
Hangul
ValueCountFrequency (%)
부 19
 
9.4%
평 18
 
8.9%
천 15
 
7.4%
동 13
 
6.4%
광 12
 
5.9%
역 12
 
5.9%
인 11
 
5.4%
시 11
 
5.4%
구 11
 
5.4%
로 11
 
5.4%
Other values (36) 70
34.5%

Interactions

2024-01-28T15:35:01.100198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:35:02.743041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장명칭소재지주소(도로명)
연번1.0001.0001.000
사업장명칭1.0001.0001.000
소재지주소(도로명)1.0001.0001.000
2024-01-28T15:35:02.808030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번판매업구분명
연번1.0001.000
판매업구분명1.0001.000

Missing values

2024-01-28T15:35:01.385618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:35:01.446627image/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.
2024-01-28T15:35:01.512727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번판매업구분명사업장명칭소재지주소(도로명)
01축산물수입판매업(주)새한 에프앤비인천광역시 부평구 부평대로 163 (부평동)
12축산물수입판매업(주)영광축산유통인천광역시 부평구 열우물로 18 (십정동, 동암역 대우 마이빌)
23축산물수입판매업(주)하나로 미트인천광역시 부평구 열우물로 18, 809호 (십정동,대우마이빌 오피스텔)
34축산물수입판매업J & P 통상인천광역시 부평구 동암광장로8번길 8 (십정동)
45축산물수입판매업동서식품(주)인천광역시 부평구 부평북로 215 (청천동)
56축산물수입판매업삼지무역 주식회사인천광역시 부평구 신트리로6번길 6 (부평동, 혜성빌딩)
67축산물수입판매업세이오 무역인천광역시 부평구 주부토로146번길 36 (갈산동)
78축산물수입판매업오킴스트레이딩인천광역시 부평구 부평대로36번길 15-1 (부평동)
89축산물수입판매업유로미트인천광역시 부평구 장제로 227 (부평동)
910축산물수입판매업중부미트넷(주)인천광역시 부평구 세월천로40번길 45, 102호 (청천동, 장미원룸)
연번판매업구분명사업장명칭소재지주소(도로명)
198<NA><NA><NA><NA>
199<NA><NA><NA><NA>
200<NA><NA><NA><NA>
201<NA><NA><NA><NA>
202<NA><NA><NA><NA>
203<NA><NA><NA><NA>
204<NA><NA><NA><NA>
205<NA><NA><NA><NA>
206<NA><NA><NA><NA>
207<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번판매업구분명사업장명칭소재지주소(도로명)# duplicates
0<NA><NA><NA><NA>197