Overview

Dataset statistics

Number of variables21
Number of observations89
Missing cells539
Missing cells (%)28.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory180.5 B

Variable types

Categorical8
Text6
DateTime1
Unsupported3
Numeric3

Alerts

소재지시설전화번호 has constant value ""Constant
축산업무구분명 has constant value ""Constant
권리주체일련번호 has constant value ""Constant
영업상태구분코드 is highly imbalanced (91.1%)Imbalance
도로명우편번호 is highly imbalanced (91.1%)Imbalance
X좌표값 is highly imbalanced (91.1%)Imbalance
Y좌표값 is highly imbalanced (91.1%)Imbalance
축산고유번호 is highly imbalanced (91.1%)Imbalance
인허가취소일자 has 89 (100.0%) missing valuesMissing
폐업일자 has 45 (50.6%) missing valuesMissing
소재지시설전화번호 has 88 (98.9%) missing valuesMissing
소재지면적정보 has 89 (100.0%) missing valuesMissing
소재지도로명주소 has 21 (23.6%) missing valuesMissing
소재지우편번호 has 2 (2.2%) missing valuesMissing
WGS84위도 has 14 (15.7%) missing valuesMissing
WGS84경도 has 14 (15.7%) missing valuesMissing
업태구분명정보 has 89 (100.0%) missing valuesMissing
권리주체일련번호 has 88 (98.9%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:22:39.916204
Analysis finished2023-12-10 22:22:40.351769
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct14
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size844.0 B
평택시
18 
여주시
12 
안성시
10 
이천시
9 
포천시
9 
Other values (9)
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)3.4%

Sample

1st row고양시
2nd row김포시
3rd row김포시
4th row안성시
5th row안성시

Common Values

ValueCountFrequency (%)
평택시 18
20.2%
여주시 12
13.5%
안성시 10
11.2%
이천시 9
10.1%
포천시 9
10.1%
화성시 8
9.0%
용인시 6
 
6.7%
양주시 5
 
5.6%
파주시 4
 
4.5%
양평군 3
 
3.4%
Other values (4) 5
 
5.6%

Length

2023-12-11T07:22:40.423271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시 18
20.2%
여주시 12
13.5%
안성시 10
11.2%
이천시 9
10.1%
포천시 9
10.1%
화성시 8
9.0%
용인시 6
 
6.7%
양주시 5
 
5.6%
파주시 4
 
4.5%
양평군 3
 
3.4%
Other values (4) 5
 
5.6%

사업장명
Text

Distinct81
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-11T07:22:40.696584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length5
Mean length6.6292135
Min length2

Characters and Unicode

Total characters590
Distinct characters112
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)83.1%

Sample

1st row충청농장
2nd row대산부화장
3rd row골드부화장
4th row동원축산
5th row농업회사법인 인주부화장 주식회사
ValueCountFrequency (%)
흥일부화장 3
 
2.9%
주식회사 3
 
2.9%
여주부화장 3
 
2.9%
농업회사법인 3
 
2.9%
기린부화장 2
 
1.9%
중원부화장 2
 
1.9%
석정부화장 2
 
1.9%
주)화인코리아 2
 
1.9%
경기도축산진흥센터 2
 
1.9%
주)마니커포천지점 2
 
1.9%
Other values (80) 80
76.9%
2023-12-11T07:22:41.136333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
화 65
 
11.0%
장 61
 
10.3%
부 59
 
10.0%
농 20
 
3.4%
주 20
 
3.4%
산 18
 
3.1%
인 17
 
2.9%
15
 
2.5%
사 15
 
2.5%
회 14
 
2.4%
Other values (102) 286
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
93.7%
Space Separator 15
 
2.5%
Open Punctuation 11
 
1.9%
Close Punctuation 11
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 65
 
11.8%
장 61
 
11.0%
부 59
 
10.7%
농 20
 
3.6%
주 20
 
3.6%
산 18
 
3.3%
인 17
 
3.1%
사 15
 
2.7%
회 14
 
2.5%
성 12
 
2.2%
Other values (99) 252
45.6%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 553
93.7%
Common 37
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 65
 
11.8%
장 61
 
11.0%
부 59
 
10.7%
농 20
 
3.6%
주 20
 
3.6%
산 18
 
3.3%
인 17
 
3.1%
사 15
 
2.7%
회 14
 
2.5%
성 12
 
2.2%
Other values (99) 252
45.6%
Common
ValueCountFrequency (%)
15
40.5%
( 11
29.7%
) 11
29.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
93.7%
ASCII 37
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
화 65
 
11.8%
장 61
 
11.0%
부 59
 
10.7%
농 20
 
3.6%
주 20
 
3.6%
산 18
 
3.3%
인 17
 
3.1%
사 15
 
2.7%
회 14
 
2.5%
성 12
 
2.2%
Other values (99) 252
45.6%
ASCII
ValueCountFrequency (%)
15
40.5%
( 11
29.7%
) 11
29.7%

인허가일자
Date

Distinct83
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size844.0 B
Minimum1989-05-15 00:00:00
Maximum2017-12-01 00:00:00
2023-12-11T07:22:41.283049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:22:41.399219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing89
Missing (%)100.0%
Memory size933.0 B

영업상태구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size844.0 B
<NA>
88 
1
 
1

Length

Max length4
Median length4
Mean length3.9662921
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
98.9%
1 1
 
1.1%

Length

2023-12-11T07:22:41.520261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:41.617208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
98.9%
1 1
 
1.1%

영업상태명
Categorical

Distinct4
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size844.0 B
폐업 등
44 
운영중
39 
휴업 등
5 
휴업
 
1

Length

Max length4
Median length4
Mean length3.5393258
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row운영중
2nd row운영중
3rd row폐업 등
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
폐업 등 44
49.4%
운영중 39
43.8%
휴업 등 5
 
5.6%
휴업 1
 
1.1%

Length

2023-12-11T07:22:41.711336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:41.814903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등 49
35.5%
폐업 44
31.9%
운영중 39
28.3%
휴업 6
 
4.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)95.5%
Missing45
Missing (%)50.6%
Infinite0
Infinite (%)0.0%
Mean20100724
Minimum20030317
Maximum20180313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:22:41.916677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030317
5-th percentile20031136
Q120061109
median20110908
Q320140433
95-th percentile20168744
Maximum20180313
Range149996
Interquartile range (IQR)79323.75

Descriptive statistics

Standard deviation44648.056
Coefficient of variation (CV)0.0022212163
Kurtosis-1.1505651
Mean20100724
Median Absolute Deviation (MAD)39638
Skewness-0.033698452
Sum8.8443185 × 108
Variance1.9934489 × 109
MonotonicityNot monotonic
2023-12-11T07:22:42.257416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
20120423 2
 
2.2%
20070928 2
 
2.2%
20160928 1
 
1.1%
20180226 1
 
1.1%
20150204 1
 
1.1%
20120710 1
 
1.1%
20140122 1
 
1.1%
20161006 1
 
1.1%
20141007 1
 
1.1%
20070703 1
 
1.1%
Other values (32) 32
36.0%
(Missing) 45
50.6%
ValueCountFrequency (%)
20030317 1
1.1%
20031013 1
1.1%
20031121 1
1.1%
20031223 1
1.1%
20040503 1
1.1%
20041224 1
1.1%
20050322 1
1.1%
20050511 1
1.1%
20050810 1
1.1%
20060508 1
1.1%
ValueCountFrequency (%)
20180313 1
1.1%
20180226 1
1.1%
20170110 1
1.1%
20161006 1
1.1%
20160928 1
1.1%
20150204 1
1.1%
20141007 1
1.1%
20140915 1
1.1%
20140729 1
1.1%
20140605 1
1.1%

소재지시설전화번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing88
Missing (%)98.9%
Memory size844.0 B
2023-12-11T07:22:42.383745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters9
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row031)8008-6395
ValueCountFrequency (%)
031)8008-6395 1
100.0%
2023-12-11T07:22:42.653039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
23.1%
3 2
15.4%
8 2
15.4%
1 1
 
7.7%
) 1
 
7.7%
- 1
 
7.7%
6 1
 
7.7%
9 1
 
7.7%
5 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
84.6%
Close Punctuation 1
 
7.7%
Dash Punctuation 1
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
27.3%
3 2
18.2%
8 2
18.2%
1 1
 
9.1%
6 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
23.1%
3 2
15.4%
8 2
15.4%
1 1
 
7.7%
) 1
 
7.7%
- 1
 
7.7%
6 1
 
7.7%
9 1
 
7.7%
5 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
23.1%
3 2
15.4%
8 2
15.4%
1 1
 
7.7%
) 1
 
7.7%
- 1
 
7.7%
6 1
 
7.7%
9 1
 
7.7%
5 1
 
7.7%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing89
Missing (%)100.0%
Memory size933.0 B

도로명우편번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size844.0 B
<NA>
88 
17118
 
1

Length

Max length5
Median length4
Mean length4.011236
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
98.9%
17118 1
 
1.1%

Length

2023-12-11T07:22:42.754975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:42.844978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
98.9%
17118 1
 
1.1%

소재지도로명주소
Text

MISSING 

Distinct60
Distinct (%)88.2%
Missing21
Missing (%)23.6%
Memory size844.0 B
2023-12-11T07:22:43.112569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length22.338235
Min length17

Characters and Unicode

Total characters1519
Distinct characters128
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)79.4%

Sample

1st row경기도 고양시 일산서구 송포로 *** (가좌동)
2nd row경기도 김포시 대곶면 대곶로***번길 ***
3rd row경기도 김포시 옹주물로 ***-* (감정동)
4th row경기도 안성시 공도읍 웅교*길 **-***
5th row경기도 안성시 공도읍 승진길 **-**
ValueCountFrequency (%)
경기도 68
19.8%
68
19.8%
평택시 16
 
4.7%
포천시 8
 
2.3%
안성시 8
 
2.3%
이천시 7
 
2.0%
여주시 7
 
2.0%
고덕면 6
 
1.7%
화성시 6
 
1.7%
고덕*로 4
 
1.2%
Other values (106) 145
42.3%
2023-12-11T07:22:43.611601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 305
20.1%
275
18.1%
도 70
 
4.6%
경 68
 
4.5%
기 68
 
4.5%
시 66
 
4.3%
로 50
 
3.3%
면 47
 
3.1%
- 36
 
2.4%
길 33
 
2.2%
Other values (118) 501
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 891
58.7%
Other Punctuation 305
 
20.1%
Space Separator 275
 
18.1%
Dash Punctuation 36
 
2.4%
Open Punctuation 6
 
0.4%
Close Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 70
 
7.9%
경 68
 
7.6%
기 68
 
7.6%
시 66
 
7.4%
로 50
 
5.6%
면 47
 
5.3%
길 33
 
3.7%
평 22
 
2.5%
성 20
 
2.2%
천 18
 
2.0%
Other values (113) 429
48.1%
Other Punctuation
ValueCountFrequency (%)
* 305
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 891
58.7%
Common 628
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 70
 
7.9%
경 68
 
7.6%
기 68
 
7.6%
시 66
 
7.4%
로 50
 
5.6%
면 47
 
5.3%
길 33
 
3.7%
평 22
 
2.5%
성 20
 
2.2%
천 18
 
2.0%
Other values (113) 429
48.1%
Common
ValueCountFrequency (%)
* 305
48.6%
275
43.8%
- 36
 
5.7%
( 6
 
1.0%
) 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 891
58.7%
ASCII 628
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 305
48.6%
275
43.8%
- 36
 
5.7%
( 6
 
1.0%
) 6
 
1.0%
Hangul
ValueCountFrequency (%)
도 70
 
7.9%
경 68
 
7.6%
기 68
 
7.6%
시 66
 
7.4%
로 50
 
5.6%
면 47
 
5.3%
길 33
 
3.7%
평 22
 
2.5%
성 20
 
2.2%
천 18
 
2.0%
Other values (113) 429
48.1%

소재지지번주소
Text

Distinct81
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-11T07:22:43.977984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length21.213483
Min length6

Characters and Unicode

Total characters1888
Distinct characters135
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)84.3%

Sample

1st row경기도 고양시 일산서구 가좌동 ***-*번지 충청농장
2nd row경기도 김포시 대곶면 송마리 ***번지
3rd row경기도 김포시 감정동 ***-**번지
4th row경기도 안성시 공도읍 건천리 **-*번지
5th row경기도 안성시 공도읍 진사리 ***-**번지
ValueCountFrequency (%)
경기도 84
19.5%
번지 84
19.5%
평택시 18
 
4.2%
여주시 11
 
2.6%
안성시 10
 
2.3%
이천시 9
 
2.1%
화성시 8
 
1.9%
고덕면 7
 
1.6%
포천시 6
 
1.4%
산 6
 
1.4%
Other values (130) 188
43.6%
2023-12-11T07:22:44.475121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
18.2%
* 297
15.7%
도 90
 
4.8%
지 89
 
4.7%
기 86
 
4.6%
경 84
 
4.4%
시 84
 
4.4%
번 84
 
4.4%
리 67
 
3.5%
- 60
 
3.2%
Other values (125) 603
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1187
62.9%
Space Separator 344
 
18.2%
Other Punctuation 297
 
15.7%
Dash Punctuation 60
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 90
 
7.6%
지 89
 
7.5%
기 86
 
7.2%
경 84
 
7.1%
시 84
 
7.1%
번 84
 
7.1%
리 67
 
5.6%
면 52
 
4.4%
동 26
 
2.2%
성 24
 
2.0%
Other values (122) 501
42.2%
Space Separator
ValueCountFrequency (%)
344
100.0%
Other Punctuation
ValueCountFrequency (%)
* 297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1187
62.9%
Common 701
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 90
 
7.6%
지 89
 
7.5%
기 86
 
7.2%
경 84
 
7.1%
시 84
 
7.1%
번 84
 
7.1%
리 67
 
5.6%
면 52
 
4.4%
동 26
 
2.2%
성 24
 
2.0%
Other values (122) 501
42.2%
Common
ValueCountFrequency (%)
344
49.1%
* 297
42.4%
- 60
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1187
62.9%
ASCII 701
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
49.1%
* 297
42.4%
- 60
 
8.6%
Hangul
ValueCountFrequency (%)
도 90
 
7.6%
지 89
 
7.5%
기 86
 
7.2%
경 84
 
7.1%
시 84
 
7.1%
번 84
 
7.1%
리 67
 
5.6%
면 52
 
4.4%
동 26
 
2.2%
성 24
 
2.0%
Other values (122) 501
42.2%

소재지우편번호
Text

MISSING 

Distinct66
Distinct (%)75.9%
Missing2
Missing (%)2.2%
Memory size844.0 B
2023-12-11T07:22:44.761018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.908046
Min length5

Characters and Unicode

Total characters514
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)58.6%

Sample

1st row411440
2nd row415855
3rd row415010
4th row456821
5th row456826
ValueCountFrequency (%)
469802 3
 
3.4%
487853 3
 
3.4%
451872 3
 
3.4%
451883 3
 
3.4%
469811 3
 
3.4%
451843 3
 
3.4%
487823 2
 
2.3%
467831 2
 
2.3%
469843 2
 
2.3%
451832 2
 
2.3%
Other values (56) 61
70.1%
2023-12-11T07:22:45.162581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 119
23.2%
8 77
15.0%
1 62
12.1%
5 51
9.9%
6 40
 
7.8%
7 37
 
7.2%
2 35
 
6.8%
3 35
 
6.8%
9 31
 
6.0%
0 26
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 513
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 119
23.2%
8 77
15.0%
1 62
12.1%
5 51
9.9%
6 40
 
7.8%
7 37
 
7.2%
2 35
 
6.8%
3 35
 
6.8%
9 31
 
6.0%
0 26
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 514
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 119
23.2%
8 77
15.0%
1 62
12.1%
5 51
9.9%
6 40
 
7.8%
7 37
 
7.2%
2 35
 
6.8%
3 35
 
6.8%
9 31
 
6.0%
0 26
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 119
23.2%
8 77
15.0%
1 62
12.1%
5 51
9.9%
6 40
 
7.8%
7 37
 
7.2%
2 35
 
6.8%
3 35
 
6.8%
9 31
 
6.0%
0 26
 
5.1%

WGS84위도
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)88.0%
Missing14
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean37.342265
Minimum36.926269
Maximum38.053278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:22:45.317199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.926269
5-th percentile36.969767
Q137.034681
median37.23382
Q337.677839
95-th percentile37.986323
Maximum38.053278
Range1.127009
Interquartile range (IQR)0.64315792

Descriptive statistics

Standard deviation0.35929996
Coefficient of variation (CV)0.0096218042
Kurtosis-0.93368368
Mean37.342265
Median Absolute Deviation (MAD)0.20830206
Skewness0.76508705
Sum2800.6699
Variance0.12909646
MonotonicityNot monotonic
2023-12-11T07:22:45.462014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.0346807072 4
 
4.5%
37.257820216 3
 
3.4%
37.0045822473 2
 
2.2%
37.0205148586 2
 
2.2%
37.8637106787 2
 
2.2%
37.9381165598 2
 
2.2%
37.3257661349 1
 
1.1%
37.9556170276 1
 
1.1%
37.7475723558 1
 
1.1%
37.9811986376 1
 
1.1%
Other values (56) 56
62.9%
(Missing) 14
 
15.7%
ValueCountFrequency (%)
36.926269215 1
1.1%
36.949826129 1
1.1%
36.9546302806 1
1.1%
36.9623813728 1
1.1%
36.9729317536 1
1.1%
36.979491102 1
1.1%
36.9820702191 1
1.1%
36.9894683481 1
1.1%
37.0045822473 2
2.2%
37.0056212215 1
1.1%
ValueCountFrequency (%)
38.0532782613 1
1.1%
38.0479505179 1
1.1%
38.0333631574 1
1.1%
37.9982801312 1
1.1%
37.9811986376 1
1.1%
37.9556170276 1
1.1%
37.9381165598 2
2.2%
37.9263603306 1
1.1%
37.8637509934 1
1.1%
37.8637106787 2
2.2%

WGS84경도
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)88.0%
Missing14
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean127.19005
Minimum126.56208
Maximum127.66243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:22:45.596634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56208
5-th percentile126.84581
Q1126.98625
median127.15086
Q3127.41266
95-th percentile127.61922
Maximum127.66243
Range1.1003422
Interquartile range (IQR)0.42641494

Descriptive statistics

Standard deviation0.26791166
Coefficient of variation (CV)0.0021063885
Kurtosis-0.79545018
Mean127.19005
Median Absolute Deviation (MAD)0.17190779
Skewness0.15149383
Sum9539.2539
Variance0.071776656
MonotonicityNot monotonic
2023-12-11T07:22:45.746462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0274289191 4
 
4.5%
127.5683283822 3
 
3.4%
126.9142821314 2
 
2.2%
126.9831398627 2
 
2.2%
127.002943646 2
 
2.2%
127.278857949 2
 
2.2%
127.4725379974 1
 
1.1%
126.8919109916 1
 
1.1%
126.8819826967 1
 
1.1%
126.9789571983 1
 
1.1%
Other values (56) 56
62.9%
(Missing) 14
 
15.7%
ValueCountFrequency (%)
126.5620846594 1
1.1%
126.6848619923 1
1.1%
126.7254134587 1
1.1%
126.7914326107 1
1.1%
126.8691128877 1
1.1%
126.8819826967 1
1.1%
126.8855302032 1
1.1%
126.8919109916 1
1.1%
126.9012155876 1
1.1%
126.9142821314 2
2.2%
ValueCountFrequency (%)
127.6624269084 1
1.1%
127.6613164742 1
1.1%
127.6517760128 1
1.1%
127.650994032 1
1.1%
127.6056046054 1
1.1%
127.5917195855 1
1.1%
127.5838949199 1
1.1%
127.5833299537 1
1.1%
127.5719450876 1
1.1%
127.5714559699 1
1.1%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing89
Missing (%)100.0%
Memory size933.0 B

X좌표값
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size844.0 B
<NA>
88 
210406.862916647
 
1

Length

Max length16
Median length4
Mean length4.1348315
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
98.9%
210406.862916647 1
 
1.1%

Length

2023-12-11T07:22:45.907816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:46.027993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
98.9%
210406.862916647 1
 
1.1%

Y좌표값
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size844.0 B
<NA>
88 
402805.623082486
 
1

Length

Max length16
Median length4
Mean length4.1348315
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
98.9%
402805.623082486 1
 
1.1%

Length

2023-12-11T07:22:46.142933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:46.248431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
98.9%
402805.623082486 1
 
1.1%

축산업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size844.0 B
부화업
89 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부화업 89
100.0%

Length

2023-12-11T07:22:46.379691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:46.499569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부화업 89
100.0%

축산고유번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size844.0 B
<NA>
88 
805
 
1

Length

Max length4
Median length4
Mean length3.988764
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
98.9%
805 1
 
1.1%

Length

2023-12-11T07:22:46.609530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:22:46.707271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
98.9%
805 1
 
1.1%

권리주체일련번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing88
Missing (%)98.9%
Memory size844.0 B
2023-12-11T07:22:46.762891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowL00
ValueCountFrequency (%)
l00 1
100.0%
2023-12-11T07:22:46.979173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
66.7%
L 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
66.7%
Uppercase Letter 1
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
66.7%
Latin 1
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
100.0%
Latin
ValueCountFrequency (%)
L 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
66.7%
L 1
33.3%

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값축산업무구분명축산고유번호권리주체일련번호
0고양시충청농장20050225<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 송포로 *** (가좌동)경기도 고양시 일산서구 가좌동 ***-*번지 충청농장41144037.693749126.725413<NA><NA><NA>부화업<NA><NA>
1김포시대산부화장19990907<NA><NA>운영중<NA><NA><NA><NA>경기도 김포시 대곶면 대곶로***번길 ***경기도 김포시 대곶면 송마리 ***번지41585537.661928126.562085<NA><NA><NA>부화업<NA><NA>
2김포시골드부화장20080118<NA><NA>폐업 등20140508<NA><NA><NA>경기도 김포시 옹주물로 ***-* (감정동)경기도 김포시 감정동 ***-**번지41501037.630663126.684862<NA><NA><NA>부화업<NA><NA>
3안성시동원축산20071227<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 공도읍 웅교*길 **-***경기도 안성시 공도읍 건천리 **-*번지45682136.972932127.181443<NA><NA><NA>부화업<NA><NA>
4안성시농업회사법인 인주부화장 주식회사20120109<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 공도읍 승진길 **-**경기도 안성시 공도읍 진사리 ***-**번지45682636.989468127.150865<NA><NA><NA>부화업<NA><NA>
5안성시동남부화장19910628<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 일죽면 서동대로 ****경기도 안성시 일죽면 송천리 ***번지45691537.089596127.470092<NA><NA><NA>부화업<NA><NA>
6안성시농업회사법인유한회사에이치비씨20110219<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 발화대길 ***-** (중리동)경기도 안성시 중리동 **-*번지45629036.979491127.289202<NA><NA><NA>부화업<NA><NA>
7안성시호일부화장19910511<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 미양면 구례골길 ***-**경기도 안성시 미양면 계륵리 ***-*번지45684336.98207127.256722<NA><NA><NA>부화업<NA><NA>
8안성시다모아부화장20111102<NA><NA>운영중<NA><NA><NA><NA>경기도 안성시 미양면 신고지길 ***경기도 안성시 미양면 고지리 ***-*번지45684236.962381127.208144<NA><NA><NA>부화업<NA><NA>
9안성시덕성부화장19930710<NA><NA>폐업 등20180313<NA><NA><NA><NA>경기도 안성시 삼죽면 배태리 **번지17514<NA><NA><NA><NA><NA>부화업<NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값축산업무구분명축산고유번호권리주체일련번호
79포천시(주)마니커포천지점20130722<NA><NA>폐업 등20140408<NA><NA><NA><NA>경기도 포천시 일동면 길명리 **-*번지48785337.92636127.291594<NA><NA><NA>부화업<NA><NA>
80포천시축석부화장20030214<NA><NA>폐업 등20041224<NA><NA><NA>경기도 포천시 창수면 포천로****번길 **-**경기도 포천시 창수면 추동리 ***번지48792137.99828127.165374<NA><NA><NA>부화업<NA><NA>
81화성시신영농원19890515<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 양감면 초록로 ***-**경기도 화성시 양감면 사창리 **-*번지44593237.104023126.974943<NA><NA><NA>부화업<NA><NA>
82화성시화산부화장19920828<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 우정읍 한말길 ***경기도 화성시 우정읍 화산리 ***번지44595337.071384126.791433<NA><NA><NA>부화업<NA><NA>
83화성시수원부화장19990707<NA><NA>폐업 등20061107<NA><NA><NA>경기도 화성시 영통로**번길 *경기도 화성시 반월동 **-*번지44597337.23382127.064897<NA><NA><NA>부화업<NA><NA>
84화성시성산부화장19891125<NA><NA>폐업 등20111124<NA><NA><NA>경기도 화성시 정남면 덕절중앙길 **-**경기도 화성시 정남면 덕절리 ***-*번지44596437.139295127.028508<NA><NA><NA>부화업<NA><NA>
85화성시남성부화장19920114<NA><NA>폐업 등20090604<NA><NA><NA><NA>경기도 화성시 북양동 ***번지445040<NA><NA><NA><NA><NA>부화업<NA><NA>
86화성시운화부화장19970718<NA><NA>폐업 등20111004<NA><NA><NA>경기도 화성시 정남면 내향로 ***-**경기도 화성시 정남면 귀래리 ***-*번지44596137.129839126.989355<NA><NA><NA>부화업<NA><NA>
87화성시삼현영농조합법인19991215<NA><NA>폐업 등20140605<NA><NA><NA>경기도 화성시 양감면 은행나무로 ***-*경기도 화성시 양감면 대양리 ***번지44593137.095669126.940082<NA><NA><NA>부화업<NA><NA>
88화성시대도부화장19910412<NA><NA>휴업 등<NA><NA><NA><NA><NA>경기도 화성시 팔탄면 율암리 산 **-** 번지445913<NA><NA><NA><NA><NA>부화업<NA><NA>