Overview

Dataset statistics

Number of variables12
Number of observations47
Missing cells66
Missing cells (%)11.7%
Duplicate rows1
Duplicate rows (%)2.1%
Total size in memory4.7 KiB
Average record size in memory102.8 B

Variable types

Categorical3
Text5
Numeric4

Dataset

Description경기도 음식물 자원화 시설현황
Author고양시
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=H8589JF8P51G1ZN893GB26609243&infSeq=1

Alerts

Dataset has 1 (2.1%) duplicate rowsDuplicates
시군명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
관리기관명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
시설유형 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
소재지우편번호 has 1 (2.1%) missing valuesMissing
소재지도로명주소 has 1 (2.1%) missing valuesMissing
소재지지번주소 has 1 (2.1%) missing valuesMissing
WGS84위도 has 1 (2.1%) missing valuesMissing
WGS84경도 has 1 (2.1%) missing valuesMissing
사업자등록번호 has 18 (38.3%) missing valuesMissing
연락처번호 has 2 (4.3%) missing valuesMissing
특이사항 has 41 (87.2%) missing valuesMissing

Reproduction

Analysis started2024-05-03 18:49:05.529409
Analysis finished2024-05-03 18:49:16.836906
Duration11.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
양주시
10 
안성시
6 
평택시
5 
광주시
5 
고양시
4 
Other values (16)
17 

Length

Max length4
Median length3
Mean length3.0638298
Min length3

Unique

Unique15 ?
Unique (%)31.9%

Sample

1st row부천시
2nd row고양시
3rd row하남시
4th row평택시
5th row평택시

Common Values

ValueCountFrequency (%)
양주시 10
21.3%
안성시 6
12.8%
평택시 5
10.6%
광주시 5
10.6%
고양시 4
 
8.5%
파주시 2
 
4.3%
부천시 1
 
2.1%
하남시 1
 
2.1%
안산시 1
 
2.1%
의정부시 1
 
2.1%
Other values (11) 11
23.4%

Length

2024-05-03T18:49:17.115155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
양주시 10
21.3%
안성시 6
12.8%
평택시 5
10.6%
광주시 5
10.6%
고양시 4
 
8.5%
파주시 2
 
4.3%
화성시 1
 
2.1%
오산시 1
 
2.1%
동두천시 1
 
2.1%
군포시 1
 
2.1%
Other values (11) 11
23.4%

시설명
Text

Distinct42
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-05-03T18:49:17.737494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length8.4893617
Min length3

Characters and Unicode

Total characters399
Distinct characters108
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)85.1%

Sample

1st row부천시자원순환센터
2nd row고양바이오매스에너지시설
3rd row음식물자원화시설
4th row경기리싸이클
5th row제일농장
ValueCountFrequency (%)
광주시음식물자원화시설 5
 
8.2%
음식물자원화시설 4
 
6.6%
자원화시설 4
 
6.6%
음식물류폐기물 2
 
3.3%
음식물류 2
 
3.3%
대광축산 1
 
1.6%
수원시 1
 
1.6%
대영실업㈜ 1
 
1.6%
두영환경 1
 
1.6%
의왕시 1
 
1.6%
Other values (39) 39
63.9%
2024-05-03T18:49:18.784577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
 
7.3%
원 21
 
5.3%
물 18
 
4.5%
자 18
 
4.5%
화 18
 
4.5%
음 16
 
4.0%
식 16
 
4.0%
설 16
 
4.0%
14
 
3.5%
주 13
 
3.3%
Other values (98) 220
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
92.2%
Space Separator 14
 
3.5%
Other Symbol 10
 
2.5%
Close Punctuation 3
 
0.8%
Open Punctuation 3
 
0.8%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
 
7.9%
원 21
 
5.7%
물 18
 
4.9%
자 18
 
4.9%
화 18
 
4.9%
음 16
 
4.3%
식 16
 
4.3%
설 16
 
4.3%
주 13
 
3.5%
이 10
 
2.7%
Other values (93) 193
52.4%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 378
94.7%
Common 21
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
 
7.7%
원 21
 
5.6%
물 18
 
4.8%
자 18
 
4.8%
화 18
 
4.8%
음 16
 
4.2%
식 16
 
4.2%
설 16
 
4.2%
주 13
 
3.4%
이 10
 
2.6%
Other values (94) 203
53.7%
Common
ValueCountFrequency (%)
14
66.7%
) 3
 
14.3%
( 3
 
14.3%
2 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
92.2%
ASCII 21
 
5.3%
None 10
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
 
7.9%
원 21
 
5.7%
물 18
 
4.9%
자 18
 
4.9%
화 18
 
4.9%
음 16
 
4.3%
식 16
 
4.3%
설 16
 
4.3%
주 13
 
3.5%
이 10
 
2.7%
Other values (93) 193
52.4%
ASCII
ValueCountFrequency (%)
14
66.7%
) 3
 
14.3%
( 3
 
14.3%
2 1
 
4.8%
None
ValueCountFrequency (%)
㈜ 10
100.0%

시설유형
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
음식물자원화시설
16 
종합재활용업
7 
중간재활용업
7 
폐기물종합재활용업
4 
사료화
2 
Other values (11)
11 

Length

Max length15
Median length11
Mean length7.1702128
Min length3

Unique

Unique11 ?
Unique (%)23.4%

Sample

1st row자동화 기계
2nd row음식물자원화시설
3rd row음식물자원화시설
4th row폐기물종합재활용업
5th row폐기물종합재활용업

Common Values

ValueCountFrequency (%)
음식물자원화시설 16
34.0%
종합재활용업 7
14.9%
중간재활용업 7
14.9%
폐기물종합재활용업 4
 
8.5%
사료화 2
 
4.3%
자동화 기계 1
 
2.1%
음식물류폐기물처리시설 1
 
2.1%
처리시설 1
 
2.1%
음식물폐기물처리시설 1
 
2.1%
공공시설 1
 
2.1%
Other values (6) 6
 
12.8%

Length

2024-05-03T18:49:19.148865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
음식물자원화시설 16
32.7%
중간재활용업 7
14.3%
종합재활용업 7
14.3%
폐기물종합재활용업 4
 
8.2%
사료화 2
 
4.1%
음식물처리시설 1
 
2.0%
음식물 1
 
2.0%
폐기물처리시설 1
 
2.0%
해당없음 1
 
2.0%
음식물처리장 1
 
2.0%
Other values (8) 8
16.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)82.6%
Missing1
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean13896.63
Minimum10252
Maximum18488
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-03T18:49:19.459295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10252
5-th percentile10346.25
Q111426
median12813
Q317512.5
95-th percentile18009.5
Maximum18488
Range8236
Interquartile range (IQR)6086.5

Descriptive statistics

Standard deviation2858.5476
Coefficient of variation (CV)0.20570077
Kurtosis-1.5169303
Mean13896.63
Median Absolute Deviation (MAD)1752
Skewness0.38737069
Sum639245
Variance8171294.2
MonotonicityNot monotonic
2024-05-03T18:49:19.862610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
12813 5
 
10.6%
11426 3
 
6.4%
10262 2
 
4.3%
17553 2
 
4.3%
18130 1
 
2.1%
16078 1
 
2.1%
17511 1
 
2.1%
17513 1
 
2.1%
12246 1
 
2.1%
16648 1
 
2.1%
Other values (28) 28
59.6%
ValueCountFrequency (%)
10252 1
2.1%
10262 2
4.3%
10599 1
2.1%
10807 1
2.1%
10896 1
2.1%
11301 1
2.1%
11409 1
2.1%
11410 1
2.1%
11413 1
2.1%
11417 1
2.1%
ValueCountFrequency (%)
18488 1
2.1%
18130 1
2.1%
18021 1
2.1%
17975 1
2.1%
17818 1
2.1%
17800 1
2.1%
17794 1
2.1%
17598 1
2.1%
17553 2
4.3%
17520 1
2.1%

소재지도로명주소
Text

MISSING 

Distinct42
Distinct (%)91.3%
Missing1
Missing (%)2.1%
Memory size508.0 B
2024-05-03T18:49:20.398296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22.5
Mean length21.630435
Min length15

Characters and Unicode

Total characters995
Distinct characters113
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

Unique41 ?
Unique (%)89.1%

Sample

1st row경기도 부천시 벌말로 122
2nd row경기도 고양시 덕양구 고양대로 1804-46
3rd row경기도 하남시 미사대로 710
4th row경기도 평택시 청북읍 청북중앙로 545-12
5th row경기도 평택시 팽성읍 근내길 42
ValueCountFrequency (%)
경기도 46
 
21.1%
양주시 10
 
4.6%
안성시 6
 
2.8%
평택시 5
 
2.3%
곤지암읍 5
 
2.3%
경충대로311번길 5
 
2.3%
36 5
 
2.3%
광주시 5
 
2.3%
은현면 5
 
2.3%
고양시 4
 
1.8%
Other values (113) 122
56.0%
2024-05-03T18:49:21.364207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
 
17.3%
경 52
 
5.2%
시 48
 
4.8%
도 47
 
4.7%
기 46
 
4.6%
1 46
 
4.6%
로 40
 
4.0%
3 31
 
3.1%
6 29
 
2.9%
길 25
 
2.5%
Other values (103) 459
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
59.0%
Decimal Number 216
 
21.7%
Space Separator 172
 
17.3%
Dash Punctuation 20
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 52
 
8.9%
시 48
 
8.2%
도 47
 
8.0%
기 46
 
7.8%
로 40
 
6.8%
길 25
 
4.3%
양 21
 
3.6%
주 19
 
3.2%
면 18
 
3.1%
번 18
 
3.1%
Other values (91) 253
43.1%
Decimal Number
ValueCountFrequency (%)
1 46
21.3%
3 31
14.4%
6 29
13.4%
2 23
10.6%
4 21
9.7%
7 16
 
7.4%
5 16
 
7.4%
0 14
 
6.5%
8 10
 
4.6%
9 10
 
4.6%
Space Separator
ValueCountFrequency (%)
172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
59.0%
Common 408
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 52
 
8.9%
시 48
 
8.2%
도 47
 
8.0%
기 46
 
7.8%
로 40
 
6.8%
길 25
 
4.3%
양 21
 
3.6%
주 19
 
3.2%
면 18
 
3.1%
번 18
 
3.1%
Other values (91) 253
43.1%
Common
ValueCountFrequency (%)
172
42.2%
1 46
 
11.3%
3 31
 
7.6%
6 29
 
7.1%
2 23
 
5.6%
4 21
 
5.1%
- 20
 
4.9%
7 16
 
3.9%
5 16
 
3.9%
0 14
 
3.4%
Other values (2) 20
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
59.0%
ASCII 408
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
42.2%
1 46
 
11.3%
3 31
 
7.6%
6 29
 
7.1%
2 23
 
5.6%
4 21
 
5.1%
- 20
 
4.9%
7 16
 
3.9%
5 16
 
3.9%
0 14
 
3.4%
Other values (2) 20
 
4.9%
Hangul
ValueCountFrequency (%)
경 52
 
8.9%
시 48
 
8.2%
도 47
 
8.0%
기 46
 
7.8%
로 40
 
6.8%
길 25
 
4.3%
양 21
 
3.6%
주 19
 
3.2%
면 18
 
3.1%
번 18
 
3.1%
Other values (91) 253
43.1%

소재지지번주소
Text

MISSING 

Distinct42
Distinct (%)91.3%
Missing1
Missing (%)2.1%
Memory size508.0 B
2024-05-03T18:49:21.878857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length21.282609
Min length16

Characters and Unicode

Total characters979
Distinct characters97
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

Unique41 ?
Unique (%)89.1%

Sample

1st row경기도 부천시 대장동 607번지
2nd row경기도 고양시 덕양구 동산동 333-1번지
3rd row경기도 하남시 신장동 27번지
4th row경기도 평택시 청북읍 고잔리 73-120번지
5th row경기도 평택시 팽성읍 두리 240-4번지
ValueCountFrequency (%)
경기도 46
 
21.1%
양주시 10
 
4.6%
안성시 6
 
2.8%
곤지암읍 5
 
2.3%
수양리 5
 
2.3%
423번지 5
 
2.3%
광주시 5
 
2.3%
은현면 5
 
2.3%
평택시 5
 
2.3%
고양시 4
 
1.8%
Other values (108) 122
56.0%
2024-05-03T18:49:23.073113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
 
17.6%
지 51
 
5.2%
도 48
 
4.9%
경 47
 
4.8%
시 47
 
4.8%
기 46
 
4.7%
번 46
 
4.7%
2 30
 
3.1%
양 27
 
2.8%
리 27
 
2.8%
Other values (87) 438
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
62.5%
Space Separator 172
 
17.6%
Decimal Number 169
 
17.3%
Dash Punctuation 26
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 51
 
8.3%
도 48
 
7.8%
경 47
 
7.7%
시 47
 
7.7%
기 46
 
7.5%
번 46
 
7.5%
양 27
 
4.4%
리 27
 
4.4%
동 24
 
3.9%
주 19
 
3.1%
Other values (75) 230
37.6%
Decimal Number
ValueCountFrequency (%)
2 30
17.8%
3 26
15.4%
1 24
14.2%
4 24
14.2%
6 15
8.9%
0 14
8.3%
7 11
 
6.5%
5 11
 
6.5%
9 8
 
4.7%
8 6
 
3.6%
Space Separator
ValueCountFrequency (%)
172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
62.5%
Common 367
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 51
 
8.3%
도 48
 
7.8%
경 47
 
7.7%
시 47
 
7.7%
기 46
 
7.5%
번 46
 
7.5%
양 27
 
4.4%
리 27
 
4.4%
동 24
 
3.9%
주 19
 
3.1%
Other values (75) 230
37.6%
Common
ValueCountFrequency (%)
172
46.9%
2 30
 
8.2%
3 26
 
7.1%
- 26
 
7.1%
1 24
 
6.5%
4 24
 
6.5%
6 15
 
4.1%
0 14
 
3.8%
7 11
 
3.0%
5 11
 
3.0%
Other values (2) 14
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
62.5%
ASCII 367
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
46.9%
2 30
 
8.2%
3 26
 
7.1%
- 26
 
7.1%
1 24
 
6.5%
4 24
 
6.5%
6 15
 
4.1%
0 14
 
3.8%
7 11
 
3.0%
5 11
 
3.0%
Other values (2) 14
 
3.8%
Hangul
ValueCountFrequency (%)
지 51
 
8.3%
도 48
 
7.8%
경 47
 
7.7%
시 47
 
7.7%
기 46
 
7.5%
번 46
 
7.5%
양 27
 
4.4%
리 27
 
4.4%
동 24
 
3.9%
주 19
 
3.1%
Other values (75) 230
37.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)91.3%
Missing1
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean37.460377
Minimum36.971484
Maximum37.945045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-03T18:49:23.447691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.971484
5-th percentile37.028399
Q137.143841
median37.370398
Q337.798289
95-th percentile37.883682
Maximum37.945045
Range0.97356104
Interquartile range (IQR)0.65444859

Descriptive statistics

Standard deviation0.32490005
Coefficient of variation (CV)0.0086731655
Kurtosis-1.5437299
Mean37.460377
Median Absolute Deviation (MAD)0.31118045
Skewness0.033487597
Sum1723.1774
Variance0.10556004
MonotonicityNot monotonic
2024-05-03T18:49:23.845158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
37.334431 5
 
10.6%
37.5423023 1
 
2.1%
37.8589965 1
 
2.1%
37.8839229 1
 
2.1%
37.8618859 1
 
2.1%
37.33777051 1
 
2.1%
37.0903168 1
 
2.1%
37.0980945 1
 
2.1%
37.0882677 1
 
2.1%
37.61121591 1
 
2.1%
Other values (32) 32
68.1%
ValueCountFrequency (%)
36.971484 1
2.1%
36.9893572 1
2.1%
37.027999 1
2.1%
37.0296 1
2.1%
37.048657 1
2.1%
37.056752 1
2.1%
37.0616831 1
2.1%
37.0744599 1
2.1%
37.0882677 1
2.1%
37.0903168 1
2.1%
ValueCountFrequency (%)
37.94504504 1
2.1%
37.8950519 1
2.1%
37.8839229 1
2.1%
37.8829613 1
2.1%
37.8706145 1
2.1%
37.8618859 1
2.1%
37.8611103 1
2.1%
37.8589965 1
2.1%
37.8559105 1
2.1%
37.8476682 1
2.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)91.3%
Missing1
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean127.06391
Minimum126.6974
Maximum127.67212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-03T18:49:24.250335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6974
5-th percentile126.76595
Q1126.91229
median127.01509
Q3127.17594
95-th percentile127.39087
Maximum127.67212
Range0.9747238
Interquartile range (IQR)0.26365678

Descriptive statistics

Standard deviation0.21290371
Coefficient of variation (CV)0.001675564
Kurtosis0.18271453
Mean127.06391
Median Absolute Deviation (MAD)0.1225995
Skewness0.68071492
Sum5844.9397
Variance0.045327989
MonotonicityNot monotonic
2024-05-03T18:49:24.671991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
127.3670477 5
 
10.6%
126.7653679 1
 
2.1%
127.077291 1
 
2.1%
127.006498 1
 
2.1%
127.004269 1
 
2.1%
126.9642594 1
 
2.1%
127.1316899 1
 
2.1%
127.3967463 1
 
2.1%
127.3732561 1
 
2.1%
127.1906942 1
 
2.1%
Other values (32) 32
68.1%
ValueCountFrequency (%)
126.6973962 1
2.1%
126.7584471 1
2.1%
126.7653679 1
2.1%
126.7676987 1
2.1%
126.8052241 1
2.1%
126.8427227 1
2.1%
126.8437567 1
2.1%
126.8777543 1
2.1%
126.878902 1
2.1%
126.8819764 1
2.1%
ValueCountFrequency (%)
127.67212 1
 
2.1%
127.4126922 1
 
2.1%
127.3967463 1
 
2.1%
127.3732561 1
 
2.1%
127.3670477 5
10.6%
127.2487669 1
 
2.1%
127.2195346 1
 
2.1%
127.1906942 1
 
2.1%
127.1316899 1
 
2.1%
127.1300775 1
 
2.1%

관리기관명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
양주시 청소행정과
10 
안성시청
6 
평택시청
5 
경기도 광주시청
5 
고양시청
4 
Other values (16)
17 

Length

Max length15
Median length10
Mean length6.2553191
Min length4

Unique

Unique15 ?
Unique (%)31.9%

Sample

1st row㈜우주엔비텍
2nd row고양시청
3rd row하남시청
4th row평택시청
5th row평택시청

Common Values

ValueCountFrequency (%)
양주시 청소행정과 10
21.3%
안성시청 6
12.8%
평택시청 5
10.6%
경기도 광주시청 5
10.6%
고양시청 4
 
8.5%
파주시청 2
 
4.3%
㈜우주엔비텍 1
 
2.1%
하남시청 1
 
2.1%
안산시청 자원순환과 1
 
2.1%
의정부시청 1
 
2.1%
Other values (11) 11
23.4%

Length

2024-05-03T18:49:25.054701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
양주시 10
14.9%
청소행정과 10
14.9%
안성시청 6
 
9.0%
평택시청 5
 
7.5%
경기도 5
 
7.5%
광주시청 5
 
7.5%
고양시청 4
 
6.0%
자원순환과 3
 
4.5%
청소자원과 2
 
3.0%
파주시청 2
 
3.0%
Other values (15) 15
22.4%

사업자등록번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing18
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean2.2562483 × 109
Minimum1.0481403 × 109
Maximum8.6287012 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-03T18:49:25.403600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0481403 × 109
5-th percentile1.1385852 × 109
Q11.258165 × 109
median1.2783005 × 109
Q31.3883008 × 109
95-th percentile6.6706808 × 109
Maximum8.6287012 × 109
Range7.5805608 × 109
Interquartile range (IQR)1.3013576 × 108

Descriptive statistics

Standard deviation2.1139346 × 109
Coefficient of variation (CV)0.93692464
Kurtosis2.6752066
Mean2.2562483 × 109
Median Absolute Deviation (MAD)29970215
Skewness1.9733572
Sum6.5431201 × 1010
Variance4.4687197 × 1018
MonotonicityNot monotonic
2024-05-03T18:49:25.825221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1288301047 1
 
2.1%
1338301049 1
 
2.1%
1278300502 1
 
2.1%
1268604618 1
 
2.1%
1118301563 1
 
2.1%
1388300797 1
 
2.1%
1259141346 1
 
2.1%
1258147787 1
 
2.1%
1258165034 1
 
2.1%
1248330287 1
 
2.1%
Other values (19) 19
40.4%
(Missing) 18
38.3%
ValueCountFrequency (%)
1048140318 1
2.1%
1118301563 1
2.1%
1169010691 1
2.1%
1248301609 1
2.1%
1248330287 1
2.1%
1258123131 1
2.1%
1258147787 1
2.1%
1258165034 1
2.1%
1258301960 1
2.1%
1259052939 1
2.1%
ValueCountFrequency (%)
8628701150 1
2.1%
6778601176 1
2.1%
6508800273 1
2.1%
6328700322 1
2.1%
4433201307 1
2.1%
3650314644 1
2.1%
1418146010 1
2.1%
1388300797 1
2.1%
1338301049 1
2.1%
1328152046 1
2.1%

연락처번호
Text

MISSING 

Distinct32
Distinct (%)71.1%
Missing2
Missing (%)4.3%
Memory size508.0 B
2024-05-03T18:49:26.278081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.288889
Min length11

Characters and Unicode

Total characters553
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

Unique30 ?
Unique (%)66.7%

Sample

1st row032-673-5377
2nd row02-350-5901
3rd row031-790-5667
4th row031-682-0449
5th row031-692-2235
ValueCountFrequency (%)
031-8082-6922 10
22.2%
031-760-2867 5
 
11.1%
031-671-4321 1
 
2.2%
031-674-9354 1
 
2.2%
031-595-5262 1
 
2.2%
031-228-3378 1
 
2.2%
031-8036-6726 1
 
2.2%
031-611-1034 1
 
2.2%
031-673-7766 1
 
2.2%
031-373-8110 1
 
2.2%
Other values (22) 22
48.9%
2024-05-03T18:49:27.155217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 90
16.3%
0 80
14.5%
3 67
12.1%
2 65
11.8%
1 57
10.3%
8 47
8.5%
6 45
8.1%
7 33
 
6.0%
9 28
 
5.1%
5 21
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 463
83.7%
Dash Punctuation 90
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
17.3%
3 67
14.5%
2 65
14.0%
1 57
12.3%
8 47
10.2%
6 45
9.7%
7 33
7.1%
9 28
 
6.0%
5 21
 
4.5%
4 20
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 90
16.3%
0 80
14.5%
3 67
12.1%
2 65
11.8%
1 57
10.3%
8 47
8.5%
6 45
8.1%
7 33
 
6.0%
9 28
 
5.1%
5 21
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 90
16.3%
0 80
14.5%
3 67
12.1%
2 65
11.8%
1 57
10.3%
8 47
8.5%
6 45
8.1%
7 33
 
6.0%
9 28
 
5.1%
5 21
 
3.8%

특이사항
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing41
Missing (%)87.2%
Memory size508.0 B
2024-05-03T18:49:27.622079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.5
Min length2

Characters and Unicode

Total characters33
Distinct characters24
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

Unique6 ?
Unique (%)100.0%

Sample

1st row해당없음
2nd row휴업
3rd row2024-03-06
4th row공공시설
5th row민간투자시설(BTO)
ValueCountFrequency (%)
해당없음 1
16.7%
휴업 1
16.7%
2024-03-06 1
16.7%
공공시설 1
16.7%
민간투자시설(bto 1
16.7%
없음 1
16.7%
2024-05-03T18:49:28.335102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
 
9.1%
공 2
 
6.1%
없 2
 
6.1%
음 2
 
6.1%
2 2
 
6.1%
- 2
 
6.1%
시 2
 
6.1%
설 2
 
6.1%
간 1
 
3.0%
O 1
 
3.0%
Other values (14) 14
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
54.5%
Decimal Number 8
24.2%
Uppercase Letter 3
 
9.1%
Dash Punctuation 2
 
6.1%
Open Punctuation 1
 
3.0%
Close Punctuation 1
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 2
11.1%
없 2
11.1%
음 2
11.1%
시 2
11.1%
설 2
11.1%
간 1
 
5.6%
자 1
 
5.6%
투 1
 
5.6%
해 1
 
5.6%
민 1
 
5.6%
Other values (3) 3
16.7%
Decimal Number
ValueCountFrequency (%)
0 3
37.5%
2 2
25.0%
6 1
 
12.5%
3 1
 
12.5%
4 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
B 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
54.5%
Common 12
36.4%
Latin 3
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 2
11.1%
없 2
11.1%
음 2
11.1%
시 2
11.1%
설 2
11.1%
간 1
 
5.6%
자 1
 
5.6%
투 1
 
5.6%
해 1
 
5.6%
민 1
 
5.6%
Other values (3) 3
16.7%
Common
ValueCountFrequency (%)
0 3
25.0%
2 2
16.7%
- 2
16.7%
( 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
4 1
 
8.3%
) 1
 
8.3%
Latin
ValueCountFrequency (%)
O 1
33.3%
T 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
54.5%
ASCII 15
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
20.0%
2 2
13.3%
- 2
13.3%
O 1
 
6.7%
T 1
 
6.7%
B 1
 
6.7%
( 1
 
6.7%
6 1
 
6.7%
3 1
 
6.7%
4 1
 
6.7%
Hangul
ValueCountFrequency (%)
공 2
11.1%
없 2
11.1%
음 2
11.1%
시 2
11.1%
설 2
11.1%
간 1
 
5.6%
자 1
 
5.6%
투 1
 
5.6%
해 1
 
5.6%
민 1
 
5.6%
Other values (3) 3
16.7%

Interactions

2024-05-03T18:49:14.224963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:11.416253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:12.362275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:13.329413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:14.550653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:11.662093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:12.593092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:13.548336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:14.843654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:11.895095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:12.824711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:13.733042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:15.093760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:12.134655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:13.059320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:49:13.963212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T18:49:28.707546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명사업자등록번호연락처번호특이사항
시군명1.0000.9920.9861.0001.0001.0000.9870.9161.0000.0001.0001.000
시설명0.9921.0000.9870.9901.0001.0000.9600.9830.9921.0000.9961.000
시설유형0.9860.9871.0000.9321.0001.0000.8800.7670.9860.0000.9921.000
소재지우편번호1.0000.9900.9321.0001.0001.0000.9500.7981.0000.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9870.9600.8800.9501.0001.0001.0000.6710.9870.0000.9851.000
WGS84경도0.9160.9830.7670.7981.0001.0000.6711.0000.9160.0000.9851.000
관리기관명1.0000.9920.9861.0001.0001.0000.9870.9161.0000.0001.0001.000
사업자등록번호0.0001.0000.0000.0001.0001.0000.0000.0000.0001.0001.000NaN
연락처번호1.0000.9960.9921.0001.0001.0000.9850.9851.0001.0001.0001.000
특이사항1.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.000
2024-05-03T18:49:29.046937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형시군명관리기관명
시설유형1.0000.8040.804
시군명0.8041.0001.000
관리기관명0.8041.0001.000
2024-05-03T18:49:29.302764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도사업자등록번호시군명시설유형관리기관명
소재지우편번호1.000-0.8630.293-0.3960.8500.6450.850
WGS84위도-0.8631.000-0.2590.2820.6820.5260.682
WGS84경도0.293-0.2591.000-0.3010.5720.3980.572
사업자등록번호-0.3960.282-0.3011.0000.0000.0000.000
시군명0.8500.6820.5720.0001.0000.8041.000
시설유형0.6450.5260.3980.0000.8041.0000.804
관리기관명0.8500.6820.5720.0001.0000.8041.000

Missing values

2024-05-03T18:49:15.505985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T18:49:16.211279image/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.
2024-05-03T18:49:16.552234image/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

시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명사업자등록번호연락처번호특이사항
0부천시부천시자원순환센터자동화 기계14400경기도 부천시 벌말로 122경기도 부천시 대장동 607번지37.542302126.765368㈜우주엔비텍1048140318032-673-5377해당없음
1고양시고양바이오매스에너지시설음식물자원화시설10599경기도 고양시 덕양구 고양대로 1804-46경기도 고양시 덕양구 동산동 333-1번지37.639524126.877754고양시청128830104702-350-5901<NA>
2하남시음식물자원화시설음식물자원화시설12941경기도 하남시 미사대로 710경기도 하남시 신장동 27번지37.546537127.219535하남시청1268304349031-790-5667<NA>
3평택시경기리싸이클폐기물종합재활용업17794경기도 평택시 청북읍 청북중앙로 545-12경기도 평택시 청북읍 고잔리 73-120번지37.056752126.890026평택시청3650314644031-682-0449<NA>
4평택시제일농장폐기물종합재활용업17975경기도 평택시 팽성읍 근내길 42경기도 평택시 팽성읍 두리 240-4번지36.971484127.05862평택시청1259052939031-692-2235휴업
5평택시청람영농조합법인폐기물종합재활용업17800경기도 평택시 청북읍 청북중앙로 459-130경기도 평택시 청북읍 고잔리 1339-3번지37.048657126.878902평택시청6508800273<NA><NA>
6평택시평택에코센터 유기성폐자원바이오가스화시설음식물류폐기물처리시설18021경기도 평택시 고덕면 도시지원1길 91경기도 평택시 고덕면 해창리 1266번지37.0296127.0151평택시청1258301960031-8024-3722<NA>
7평택시㈜그린월드폐기물종합재활용업17818경기도 평택시 오성면 청오로 255-7경기도 평택시 오성면 양교리 140-1번지37.027999126.973409평택시청1258123131031-682-4068<NA>
8파주시운정환경관리센터음식물자원화시설10896경기도 파주시 가람로150번길 41-34경기도 파주시 와동동 1503번지37.737143126.767699파주시청1288300937031-940-4771<NA>
9안산시안산시 음식물류폐기물 자원화시설음식물자원화시설15607경기도 안산시 단원구 해봉로 45경기도 안산시 단원구 성곡동 621-2번지37.307312126.758447안산시청 자원순환과6778601176031-408-5344<NA>
시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명사업자등록번호연락처번호특이사항
37안성시이엘투엘㈜음식물자원화시설17553경기도 안성시 원곡면 삼봉로 788-6경기도 안성시 원곡면 산하리 395번지37.07446127.130077안성시청1258165034031-611-1034<NA>
38안성시㈜케이비아이울트라음식물자원화시설17598경기도 안성시 미양면 구례골길 78경기도 안성시 미양면 구례리 76-2번지36.989357127.248767안성시청1258147787031-671-4321<NA>
39안성시씨에프음식물자원화시설17520경기도 안성시 죽산면 걸미로 766-29경기도 안성시 죽산면 장원리 산72번지37.061683127.412692안성시청1259141346031-673-7766<NA>
40안양시음식물자원화시설공공시설14014경기도 안양시 만안구 박달로 232경기도 안양시 만안구 박달동 751-7번지37.403025126.881976자원순환과<NA>031-8045-2257<NA>
41과천시과천시자원정화센터음식물처리시설13824경기도 과천시 구리안로 177경기도 과천시 갈현동 205-1번지37.407411126.993331과천시청138830079702-3677-2238<NA>
42화성시화성동탄2 크린에너지센터음식물류폐기물처리시설(공공)18488경기도 화성시 동탄대로9길 76경기도 화성시 송동 681-244번지37.176091127.095384화성시환경사업소1118301563031-5189-6832공공시설
43여주시음식물자원화센터음식물처리장12666경기도 여주시 점동면 장여로 1381-60경기도 여주시 점동면 처리 739-63번지37.23203127.67212여주시 자원순환과1268604618031-881-1945민간투자시설(BTO)
44군포시해당없음해당없음<NA><NA><NA><NA><NA>해당없음<NA><NA><NA>
45동두천시음식물류폐기물 자원화시설폐기물처리시설11301경기도 동두천시 봉동로 27경기도 동두천시 상봉암동 173번지37.945045127.056591동두천시1278300502031-860-2252없음
46시흥시음식물류 자원화시설음식물 자원화시설15099경기도 시흥시 공단2대로 14경기도 시흥시 정왕동 2163번지37.333387126.697396시흥시청1338301049031-310-3102<NA>

Duplicate rows

Most frequently occurring

시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명사업자등록번호연락처번호특이사항# duplicates
0광주시광주시음식물자원화시설음식물자원화시설12813경기도 광주시 곤지암읍 경충대로311번길 36경기도 광주시 곤지암읍 수양리 423번지37.334431127.367048경기도 광주시청<NA>031-760-2867<NA>5