Overview

Dataset statistics

Number of variables10
Number of observations176
Missing cells186
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory85.8 B

Variable types

Categorical2
Text3
Numeric4
Unsupported1

Alerts

영업상태명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
시설장비보유내역 has 176 (100.0%) missing valuesMissing
소재지도로명주소 has 8 (4.5%) missing valuesMissing
소재지우편번호 has 2 (1.1%) missing valuesMissing
시설장비보유내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 20:59:11.725917
Analysis finished2023-12-10 20:59:17.092299
Duration5.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
안양시
34 
성남시
18 
이천시
12 
화성시
11 
평택시
11 
Other values (22)
90 

Length

Max length4
Median length3
Mean length3.0113636
Min length3

Unique

Unique6 ?
Unique (%)3.4%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row과천시
5th row과천시

Common Values

ValueCountFrequency (%)
안양시 34
19.3%
성남시 18
 
10.2%
이천시 12
 
6.8%
화성시 11
 
6.2%
평택시 11
 
6.2%
광명시 11
 
6.2%
안성시 10
 
5.7%
수원시 9
 
5.1%
포천시 8
 
4.5%
의왕시 7
 
4.0%
Other values (17) 45
25.6%

Length

2023-12-11T05:59:17.190480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안양시 34
19.3%
성남시 18
 
10.2%
이천시 12
 
6.8%
화성시 11
 
6.2%
평택시 11
 
6.2%
광명시 11
 
6.2%
안성시 10
 
5.7%
수원시 9
 
5.1%
포천시 8
 
4.5%
의왕시 7
 
4.0%
Other values (17) 45
25.6%

사업장명
Text

Distinct170
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T05:59:17.446071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length8.8238636
Min length3

Characters and Unicode

Total characters1553
Distinct characters186
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)93.2%

Sample

1st row우창지하수
2nd row주식회사 엑스지오(031-907-1400)
3rd row(주)코리아지오테크
4th row한주엔지니어링(주)
5th row(주)지지컨설턴트
ValueCountFrequency (%)
주식회사 12
 
6.2%
신수건설(주 2
 
1.0%
재단법인 2
 
1.0%
주)한맥이앤씨 2
 
1.0%
한국지질조사탐사업협동조합 2
 
1.0%
㈜한국지우 2
 
1.0%
주)지우엔지니어링 2
 
1.0%
주)강림건설 2
 
1.0%
주)하이드로 1
 
0.5%
합)두물지하수개발 1
 
0.5%
Other values (164) 164
85.4%
2023-12-11T05:59:17.905432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 155
 
10.0%
( 138
 
8.9%
) 138
 
8.9%
지 112
 
7.2%
엔 51
 
3.3%
어 45
 
2.9%
링 43
 
2.8%
니 43
 
2.8%
이 31
 
2.0%
사 28
 
1.8%
Other values (176) 769
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1243
80.0%
Open Punctuation 138
 
8.9%
Close Punctuation 138
 
8.9%
Space Separator 16
 
1.0%
Decimal Number 10
 
0.6%
Other Symbol 6
 
0.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 155
 
12.5%
지 112
 
9.0%
엔 51
 
4.1%
어 45
 
3.6%
링 43
 
3.5%
니 43
 
3.5%
이 31
 
2.5%
사 28
 
2.3%
개 26
 
2.1%
발 26
 
2.1%
Other values (165) 683
54.9%
Decimal Number
ValueCountFrequency (%)
0 4
40.0%
1 2
20.0%
7 1
 
10.0%
4 1
 
10.0%
9 1
 
10.0%
3 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1249
80.4%
Common 304
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 155
 
12.4%
지 112
 
9.0%
엔 51
 
4.1%
어 45
 
3.6%
링 43
 
3.4%
니 43
 
3.4%
이 31
 
2.5%
사 28
 
2.2%
개 26
 
2.1%
발 26
 
2.1%
Other values (166) 689
55.2%
Common
ValueCountFrequency (%)
( 138
45.4%
) 138
45.4%
16
 
5.3%
0 4
 
1.3%
1 2
 
0.7%
- 2
 
0.7%
7 1
 
0.3%
4 1
 
0.3%
9 1
 
0.3%
3 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1243
80.0%
ASCII 304
 
19.6%
None 6
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 155
 
12.5%
지 112
 
9.0%
엔 51
 
4.1%
어 45
 
3.6%
링 43
 
3.5%
니 43
 
3.5%
이 31
 
2.5%
사 28
 
2.3%
개 26
 
2.1%
발 26
 
2.1%
Other values (165) 683
54.9%
ASCII
ValueCountFrequency (%)
( 138
45.4%
) 138
45.4%
16
 
5.3%
0 4
 
1.3%
1 2
 
0.7%
- 2
 
0.7%
7 1
 
0.3%
4 1
 
0.3%
9 1
 
0.3%
3 1
 
0.3%
None
ValueCountFrequency (%)
㈜ 6
100.0%

인허가일자
Real number (ℝ)

Distinct159
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20077641
Minimum19970926
Maximum20180319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T05:59:18.087722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970926
5-th percentile19971024
Q120011103
median20071152
Q320140766
95-th percentile20170923
Maximum20180319
Range209393
Interquartile range (IQR)129662.25

Descriptive statistics

Standard deviation68247.358
Coefficient of variation (CV)0.0033991722
Kurtosis-1.3535789
Mean20077641
Median Absolute Deviation (MAD)60387.5
Skewness-0.11080304
Sum3.5336648 × 109
Variance4.6577019 × 109
MonotonicityNot monotonic
2023-12-11T05:59:18.245965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19970926 5
 
2.8%
19971024 3
 
1.7%
20010612 2
 
1.1%
20011016 2
 
1.1%
19980217 2
 
1.1%
20130506 2
 
1.1%
19980219 2
 
1.1%
20140929 2
 
1.1%
20161230 2
 
1.1%
20060306 2
 
1.1%
Other values (149) 152
86.4%
ValueCountFrequency (%)
19970926 5
2.8%
19971011 2
 
1.1%
19971024 3
1.7%
19971104 1
 
0.6%
19971126 1
 
0.6%
19980211 1
 
0.6%
19980217 2
 
1.1%
19980219 2
 
1.1%
19980307 1
 
0.6%
19980330 1
 
0.6%
ValueCountFrequency (%)
20180319 1
0.6%
20180314 1
0.6%
20180313 1
0.6%
20180222 1
0.6%
20180214 1
0.6%
20180208 1
0.6%
20171030 1
0.6%
20171016 1
0.6%
20170925 1
0.6%
20170922 1
0.6%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
운영중
176 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 176
100.0%

Length

2023-12-11T05:59:18.417449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:59:18.581012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 176
100.0%

시설장비보유내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

소재지도로명주소
Text

MISSING 

Distinct162
Distinct (%)96.4%
Missing8
Missing (%)4.5%
Memory size1.5 KiB
2023-12-11T05:59:18.901040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length28.571429
Min length14

Characters and Unicode

Total characters4800
Distinct characters262
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)93.5%

Sample

1st row경기도 가평군 청평면 은고개로 36, 202호
2nd row경기도 고양시 일산동구 호수로 358-39, 101동 516호 (백석동, 동문굿모닝타워)
3rd row경기도 과천시 별양상가1로 35
4th row경기도 과천시 별양상가2로 14
5th row경기도 과천시 별양로 85, 301-3호 (별양동, 복합상가)
ValueCountFrequency (%)
경기도 167
 
16.4%
안양시 32
 
3.1%
동안구 29
 
2.8%
성남시 17
 
1.7%
이천시 12
 
1.2%
평택시 11
 
1.1%
광명시 11
 
1.1%
수원시 9
 
0.9%
안성시 9
 
0.9%
관양동 9
 
0.9%
Other values (501) 714
70.0%
2023-12-11T05:59:19.513207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
856
 
17.8%
기 178
 
3.7%
시 174
 
3.6%
경 171
 
3.6%
도 170
 
3.5%
동 163
 
3.4%
1 156
 
3.2%
로 149
 
3.1%
( 116
 
2.4%
) 116
 
2.4%
Other values (252) 2551
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2754
57.4%
Space Separator 856
 
17.8%
Decimal Number 793
 
16.5%
Open Punctuation 116
 
2.4%
Close Punctuation 116
 
2.4%
Other Punctuation 111
 
2.3%
Dash Punctuation 34
 
0.7%
Uppercase Letter 17
 
0.4%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 178
 
6.5%
시 174
 
6.3%
경 171
 
6.2%
도 170
 
6.2%
동 163
 
5.9%
로 149
 
5.4%
안 113
 
4.1%
양 76
 
2.8%
구 71
 
2.6%
호 67
 
2.4%
Other values (231) 1422
51.6%
Decimal Number
ValueCountFrequency (%)
1 156
19.7%
2 103
13.0%
0 94
11.9%
3 91
11.5%
6 85
10.7%
4 73
9.2%
5 54
 
6.8%
8 50
 
6.3%
9 47
 
5.9%
7 40
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S 6
35.3%
K 5
29.4%
B 4
23.5%
D 1
 
5.9%
A 1
 
5.9%
Space Separator
ValueCountFrequency (%)
856
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Other Punctuation
ValueCountFrequency (%)
, 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2754
57.4%
Common 2026
42.2%
Latin 20
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 178
 
6.5%
시 174
 
6.3%
경 171
 
6.2%
도 170
 
6.2%
동 163
 
5.9%
로 149
 
5.4%
안 113
 
4.1%
양 76
 
2.8%
구 71
 
2.6%
호 67
 
2.4%
Other values (231) 1422
51.6%
Common
ValueCountFrequency (%)
856
42.3%
1 156
 
7.7%
( 116
 
5.7%
) 116
 
5.7%
, 111
 
5.5%
2 103
 
5.1%
0 94
 
4.6%
3 91
 
4.5%
6 85
 
4.2%
4 73
 
3.6%
Other values (5) 225
 
11.1%
Latin
ValueCountFrequency (%)
S 6
30.0%
K 5
25.0%
B 4
20.0%
n 3
15.0%
D 1
 
5.0%
A 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2754
57.4%
ASCII 2046
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
856
41.8%
1 156
 
7.6%
( 116
 
5.7%
) 116
 
5.7%
, 111
 
5.4%
2 103
 
5.0%
0 94
 
4.6%
3 91
 
4.4%
6 85
 
4.2%
4 73
 
3.6%
Other values (11) 245
 
12.0%
Hangul
ValueCountFrequency (%)
기 178
 
6.5%
시 174
 
6.3%
경 171
 
6.2%
도 170
 
6.2%
동 163
 
5.9%
로 149
 
5.4%
안 113
 
4.1%
양 76
 
2.8%
구 71
 
2.6%
호 67
 
2.4%
Other values (231) 1422
51.6%

소재지지번주소
Text

Distinct171
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T05:59:19.853347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length26.386364
Min length15

Characters and Unicode

Total characters4644
Distinct characters236
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)94.3%

Sample

1st row경기도 가평군 청평면 청평리 333-9번지 전주이씨도사공청평종중회관 202호
2nd row경기도 고양시 일산동구 백석동 동문굿모닝타워1차 101동 516호
3rd row경기도 과천시 별양동 1-4번지
4th row경기도 과천시 별양동 1-13번지 제일쇼핑빌딩 602호
5th row경기도 과천시 별양동 7번지
ValueCountFrequency (%)
경기도 176
 
18.0%
안양시 34
 
3.5%
동안구 31
 
3.2%
관양동 21
 
2.1%
성남시 18
 
1.8%
이천시 12
 
1.2%
화성시 11
 
1.1%
광명시 11
 
1.1%
평택시 11
 
1.1%
안성시 10
 
1.0%
Other values (445) 643
65.7%
2023-12-11T05:59:20.377433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
806
 
17.4%
1 199
 
4.3%
동 187
 
4.0%
도 183
 
3.9%
기 180
 
3.9%
지 178
 
3.8%
경 177
 
3.8%
시 176
 
3.8%
번 173
 
3.7%
- 133
 
2.9%
Other values (226) 2252
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2763
59.5%
Decimal Number 916
 
19.7%
Space Separator 806
 
17.4%
Dash Punctuation 133
 
2.9%
Uppercase Letter 20
 
0.4%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 187
 
6.8%
도 183
 
6.6%
기 180
 
6.5%
지 178
 
6.4%
경 177
 
6.4%
시 176
 
6.4%
번 173
 
6.3%
안 100
 
3.6%
양 81
 
2.9%
구 73
 
2.6%
Other values (202) 1255
45.4%
Decimal Number
ValueCountFrequency (%)
1 199
21.7%
2 104
11.4%
0 100
10.9%
3 95
10.4%
5 91
9.9%
4 90
9.8%
9 71
 
7.8%
6 67
 
7.3%
7 56
 
6.1%
8 43
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
S 6
30.0%
K 5
25.0%
B 3
15.0%
D 2
 
10.0%
T 1
 
5.0%
I 1
 
5.0%
A 1
 
5.0%
F 1
 
5.0%
Space Separator
ValueCountFrequency (%)
806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2763
59.5%
Common 1860
40.1%
Latin 21
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 187
 
6.8%
도 183
 
6.6%
기 180
 
6.5%
지 178
 
6.4%
경 177
 
6.4%
시 176
 
6.4%
번 173
 
6.3%
안 100
 
3.6%
양 81
 
2.9%
구 73
 
2.6%
Other values (202) 1255
45.4%
Common
ValueCountFrequency (%)
806
43.3%
1 199
 
10.7%
- 133
 
7.2%
2 104
 
5.6%
0 100
 
5.4%
3 95
 
5.1%
5 91
 
4.9%
4 90
 
4.8%
9 71
 
3.8%
6 67
 
3.6%
Other values (5) 104
 
5.6%
Latin
ValueCountFrequency (%)
S 6
28.6%
K 5
23.8%
B 3
14.3%
D 2
 
9.5%
T 1
 
4.8%
I 1
 
4.8%
n 1
 
4.8%
A 1
 
4.8%
F 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2763
59.5%
ASCII 1881
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
806
42.8%
1 199
 
10.6%
- 133
 
7.1%
2 104
 
5.5%
0 100
 
5.3%
3 95
 
5.1%
5 91
 
4.8%
4 90
 
4.8%
9 71
 
3.8%
6 67
 
3.6%
Other values (14) 125
 
6.6%
Hangul
ValueCountFrequency (%)
동 187
 
6.8%
도 183
 
6.6%
기 180
 
6.5%
지 178
 
6.4%
경 177
 
6.4%
시 176
 
6.4%
번 173
 
6.3%
안 100
 
3.6%
양 81
 
2.9%
구 73
 
2.6%
Other values (202) 1255
45.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct134
Distinct (%)77.0%
Missing2
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean14987.046
Minimum10076
Maximum18593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T05:59:20.555425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10076
5-th percentile11183.65
Q113591.25
median14292.5
Q317269.5
95-th percentile18292.8
Maximum18593
Range8517
Interquartile range (IQR)3678.25

Descriptive statistics

Standard deviation2115.9968
Coefficient of variation (CV)0.14118839
Kurtosis-0.92935644
Mean14987.046
Median Absolute Deviation (MAD)1673
Skewness-0.011034408
Sum2607746
Variance4477442.6
MonotonicityNot monotonic
2023-12-11T05:59:20.707030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14056 8
 
4.5%
13207 5
 
2.8%
14059 5
 
2.8%
14912 4
 
2.3%
14057 3
 
1.7%
13837 3
 
1.7%
14303 3
 
1.7%
17783 3
 
1.7%
13951 3
 
1.7%
16006 3
 
1.7%
Other values (124) 134
76.1%
ValueCountFrequency (%)
10076 1
0.6%
10449 1
0.6%
11007 1
0.6%
11106 1
0.6%
11139 1
0.6%
11155 1
0.6%
11161 1
0.6%
11180 1
0.6%
11183 1
0.6%
11184 1
0.6%
ValueCountFrequency (%)
18593 1
0.6%
18587 1
0.6%
18533 1
0.6%
18529 1
0.6%
18387 1
0.6%
18327 1
0.6%
18315 1
0.6%
18303 1
0.6%
18298 1
0.6%
18290 1
0.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct149
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.361585
Minimum36.963029
Maximum38.090783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T05:59:20.888689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.963029
5-th percentile37.007899
Q137.265283
median37.390833
Q337.439938
95-th percentile37.806136
Maximum38.090783
Range1.127754
Interquartile range (IQR)0.17465515

Descriptive statistics

Standard deviation0.20184963
Coefficient of variation (CV)0.0054025982
Kurtosis1.8522796
Mean37.361585
Median Absolute Deviation (MAD)0.079945518
Skewness0.64301748
Sum6575.6389
Variance0.040743274
MonotonicityNot monotonic
2023-12-11T05:59:21.276810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.401417847 6
 
3.4%
37.4399380267 5
 
2.8%
37.4009449504 3
 
1.7%
37.0552963832 3
 
1.7%
37.4593513551 3
 
1.7%
37.3925290805 2
 
1.1%
37.3913009562 2
 
1.1%
37.2779675488 2
 
1.1%
37.0013036426 2
 
1.1%
37.3653375072 2
 
1.1%
Other values (139) 146
83.0%
ValueCountFrequency (%)
36.9630287702 1
0.6%
36.9759617295 1
0.6%
36.9812440753 1
0.6%
36.9872796245 1
0.6%
37.0013036426 2
1.1%
37.0016329451 1
0.6%
37.0028851713 1
0.6%
37.0040233809 1
0.6%
37.0091906402 1
0.6%
37.0102148309 1
0.6%
ValueCountFrequency (%)
38.0907828081 1
0.6%
38.0591926564 1
0.6%
37.9539627859 1
0.6%
37.8717779516 1
0.6%
37.8509724685 1
0.6%
37.8247561886 1
0.6%
37.8172842264 1
0.6%
37.8153666932 1
0.6%
37.8101178243 1
0.6%
37.8048086615 1
0.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct149
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07359
Minimum126.70363
Maximum127.6591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T05:59:21.440032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70363
5-th percentile126.7939
Q1126.9537
median126.99332
Q3127.17509
95-th percentile127.46055
Maximum127.6591
Range0.95547089
Interquartile range (IQR)0.22139242

Descriptive statistics

Standard deviation0.20214391
Coefficient of variation (CV)0.0015907626
Kurtosis0.34029584
Mean127.07359
Median Absolute Deviation (MAD)0.11756683
Skewness0.90299151
Sum22364.952
Variance0.040862162
MonotonicityNot monotonic
2023-12-11T05:59:21.591728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9676447726 6
 
3.4%
127.1776552165 5
 
2.8%
126.9908313688 3
 
1.7%
127.0566772224 3
 
1.7%
126.874845259 3
 
1.7%
126.9540864788 2
 
1.1%
126.9728666221 2
 
1.1%
127.4429861636 2
 
1.1%
127.1108906378 2
 
1.1%
127.1062400098 2
 
1.1%
Other values (139) 146
83.0%
ValueCountFrequency (%)
126.7036340527 1
0.6%
126.7759114601 1
0.6%
126.7818295568 1
0.6%
126.7864895442 1
0.6%
126.7908037221 1
0.6%
126.7909103658 1
0.6%
126.7912198651 2
1.1%
126.7921357989 1
0.6%
126.7944918442 1
0.6%
126.7972421404 1
0.6%
ValueCountFrequency (%)
127.6591049402 1
0.6%
127.6411969097 1
0.6%
127.6336343478 1
0.6%
127.6167450707 1
0.6%
127.5250825797 1
0.6%
127.5015931228 1
0.6%
127.499654595 1
0.6%
127.4981433695 1
0.6%
127.4791272312 1
0.6%
127.4543547492 1
0.6%

Interactions

2023-12-11T05:59:16.247734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:14.582546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.343792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.818230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.346976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:14.920659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.454157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.932971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.445676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.112432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.591827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.039519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.541217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.238179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.705886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.144226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T05:59:21.695998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자소재지우편번호WGS84위도WGS84경도
시군명1.0000.3890.9880.9650.954
인허가일자0.3891.0000.2250.3640.388
소재지우편번호0.9880.2251.0000.9250.887
WGS84위도0.9650.3640.9251.0000.758
WGS84경도0.9540.3880.8870.7581.000
2023-12-11T05:59:21.827438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도시군명
인허가일자1.0000.014-0.055-0.0070.156
소재지우편번호0.0141.000-0.817-0.1160.872
WGS84위도-0.055-0.8171.000-0.1660.763
WGS84경도-0.007-0.116-0.1661.0000.724
시군명0.1560.8720.7630.7241.000

Missing values

2023-12-11T05:59:16.668618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T05:59:16.872606image/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.
2023-12-11T05:59:17.028667image/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

시군명사업장명인허가일자영업상태명시설장비보유내역소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군우창지하수20161114운영중<NA>경기도 가평군 청평면 은고개로 36, 202호경기도 가평군 청평면 청평리 333-9번지 전주이씨도사공청평종중회관 202호1245237.738748127.423724
1고양시주식회사 엑스지오(031-907-1400)20131106운영중<NA>경기도 고양시 일산동구 호수로 358-39, 101동 516호 (백석동, 동문굿모닝타워)경기도 고양시 일산동구 백석동 동문굿모닝타워1차 101동 516호1044937.640383126.78649
2과천시(주)코리아지오테크19980401운영중<NA>경기도 과천시 별양상가1로 35경기도 과천시 별양동 1-4번지1383737.428471126.993505
3과천시한주엔지니어링(주)19990305운영중<NA>경기도 과천시 별양상가2로 14경기도 과천시 별양동 1-13번지 제일쇼핑빌딩 602호1383737.427246126.992951
4과천시(주)지지컨설턴트19970926운영중<NA>경기도 과천시 별양로 85, 301-3호 (별양동, 복합상가)경기도 과천시 별양동 7번지1383837.426471126.993945
5과천시(주)강동엔지니어링20180314운영중<NA>경기도 과천시 별양상가1로 31, 제일상가 4층 409호 (별양동)경기도 과천시 별양동 1-3번지 제일상가빌딩 409호1383737.428606126.993143
6광명시동서지하개발19971011운영중<NA>경기도 광명시 범안로 998, 401호 (하안동,녹원빌딩)경기도 광명시 하안동 302번지 녹원빌딩 401호1430337.459351126.874845
7광명시(주)유진지질20171016운영중<NA>경기도 광명시 서독로 96경기도 광명시 가학동 556-3번지 2층1433937.416245126.850406
8광명시주식회사 아주엔지니어링20170203운영중<NA>경기도 광명시 하안로 60, 비동 908호 (소하동, 광명테크노파크)경기도 광명시 소하동 1345번지 광명테크노파크 비동 908호1432237.445018126.894612
9광명시(주)삼영개발19971024운영중<NA>경기도 광명시 도덕로 12 (광명동,정혜빌딩2층)경기도 광명시 광명동 747-4번지 정혜빌딩2층1428237.467484126.849205
시군명사업장명인허가일자영업상태명시설장비보유내역소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
166화성시(주)무한건설20010307운영중<NA>경기도 화성시 봉담읍 샘마을길 26경기도 화성시 봉담읍 상리 21-19번지1831537.217855126.949952
167화성시(주)다한엔지니어링20170725운영중<NA>경기도 화성시 봉담읍 고시길 33경기도 화성시 봉담읍 수기리 1-163번지1832737.205827126.98015
168화성시(주)도성기술공사19991007운영중<NA><NA>경기도 화성시 매송면 천천리 35-1번지1829037.251239126.952284
169화성시(합)두물지하수개발20020703운영중<NA>경기도 화성시 향남읍 삼천병마로 173-3경기도 화성시 향남읍 평리 172번지1859337.128725126.908354
170화성시신수건설(주)20161201운영중<NA>경기도 화성시 팔탄면 푸른들판로 651, 2층경기도 화성시 팔탄면 구장리 113-10번지 2층1852937.166224126.894797
171화성시신수건설(주)20161201운영중<NA>경기도 화성시 진안북길79번길 24-9, 2층 202호 (진안동)경기도 화성시 진안동 43-1번지 2층 202호1838737.22535127.034555
172화성시한일지하수개발(주)20020226운영중<NA>경기도 화성시 향남읍 삼천병마로 265-6경기도 화성시 향남읍 장짐리 270-1번지1858737.136332126.911383
173화성시(주)녹산엔지니어링20090122운영중<NA>경기도 화성시 봉담읍 오래4길 20경기도 화성시 봉담읍 동화리 558-6번지1830337.21974126.955426
174화성시(주)고려기초연구소20161230운영중<NA>경기도 화성시 팔탄면 신양2길 65경기도 화성시 팔탄면 가재리 116-2번지1853337.149419126.928871
175화성시쌍진지하개발(주)19971024운영중<NA><NA>경기도 화성시 우정면 조암리 247-1번지<NA>37.084283126.821416