Overview

Dataset statistics

Number of variables8
Number of observations654
Missing cells28
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.9 KiB
Average record size in memory67.2 B

Variable types

Categorical1
Text4
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
소재지도로명주소 has 7 (1.1%) missing valuesMissing
소재지우편번호 has 7 (1.1%) missing valuesMissing
WGS84위도 has 7 (1.1%) missing valuesMissing
WGS84경도 has 7 (1.1%) missing valuesMissing
시설명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:34:12.545827
Analysis finished2024-04-20 18:34:15.333548
Duration2.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설립구분명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
공립
567 
사립
87 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 567
86.7%
사립 87
 
13.3%

Length

2024-04-21T03:34:15.388039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:34:15.464945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 567
86.7%
사립 87
 
13.3%

시설명
Text

UNIQUE 

Distinct654
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T03:34:15.659400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3272171
Min length5

Characters and Unicode

Total characters3484
Distinct characters234
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique654 ?
Unique (%)100.0%

Sample

1st row고양송산중학교
2nd row금촌중학교
3rd row논곡중학교
4th row단원중학교
5th row두일중학교
ValueCountFrequency (%)
고양송산중학교 1
 
0.2%
부천일신중학교 1
 
0.2%
영일중학교 1
 
0.2%
호매실중학교 1
 
0.2%
영통중학교 1
 
0.2%
원천중학교 1
 
0.2%
율전중학교 1
 
0.2%
율현중학교 1
 
0.2%
이목중학교 1
 
0.2%
천천중학교 1
 
0.2%
Other values (644) 644
98.5%
2024-04-21T03:34:15.988654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 665
19.1%
교 662
19.0%
학 657
18.9%
동 41
 
1.2%
산 39
 
1.1%
천 38
 
1.1%
성 37
 
1.1%
양 36
 
1.0%
원 36
 
1.0%
곡 33
 
0.9%
Other values (224) 1240
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3484
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 665
19.1%
교 662
19.0%
학 657
18.9%
동 41
 
1.2%
산 39
 
1.1%
천 38
 
1.1%
성 37
 
1.1%
양 36
 
1.0%
원 36
 
1.0%
곡 33
 
0.9%
Other values (224) 1240
35.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3484
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 665
19.1%
교 662
19.0%
학 657
18.9%
동 41
 
1.2%
산 39
 
1.1%
천 38
 
1.1%
성 37
 
1.1%
양 36
 
1.0%
원 36
 
1.0%
곡 33
 
0.9%
Other values (224) 1240
35.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3484
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 665
19.1%
교 662
19.0%
학 657
18.9%
동 41
 
1.2%
산 39
 
1.1%
천 38
 
1.1%
성 37
 
1.1%
양 36
 
1.0%
원 36
 
1.0%
곡 33
 
0.9%
Other values (224) 1240
35.6%

전화번호
Text

UNIQUE 

Distinct654
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T03:34:16.200619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length12.166667
Min length10

Characters and Unicode

Total characters7957
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique654 ?
Unique (%)100.0%

Sample

1st row031-910-1319
2nd row031-940-2311
3rd row070-7097-1390
4th row070-5202-2206
5th row031-940-6900
ValueCountFrequency (%)
031-910-1319 1
 
0.2%
070-7099-8711 1
 
0.2%
031-203-0053 1
 
0.2%
031-8025-5500 1
 
0.2%
031-203-2093 1
 
0.2%
031-211-4292 1
 
0.2%
031-548-8106 1
 
0.2%
031-298-9672 1
 
0.2%
031-547-5210 1
 
0.2%
031-547-5000 1
 
0.2%
Other values (644) 644
98.5%
2024-04-21T03:34:16.550328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1453
18.3%
- 1304
16.4%
1 1038
13.0%
3 1027
12.9%
2 536
 
6.7%
7 508
 
6.4%
8 460
 
5.8%
9 428
 
5.4%
5 421
 
5.3%
6 398
 
5.0%
Other values (3) 384
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6647
83.5%
Dash Punctuation 1304
 
16.4%
Other Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1453
21.9%
1 1038
15.6%
3 1027
15.5%
2 536
 
8.1%
7 508
 
7.6%
8 460
 
6.9%
9 428
 
6.4%
5 421
 
6.3%
6 398
 
6.0%
4 378
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 1304
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7957
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1453
18.3%
- 1304
16.4%
1 1038
13.0%
3 1027
12.9%
2 536
 
6.7%
7 508
 
6.4%
8 460
 
5.8%
9 428
 
5.4%
5 421
 
5.3%
6 398
 
5.0%
Other values (3) 384
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7957
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1453
18.3%
- 1304
16.4%
1 1038
13.0%
3 1027
12.9%
2 536
 
6.7%
7 508
 
6.4%
8 460
 
5.8%
9 428
 
5.4%
5 421
 
5.3%
6 398
 
5.0%
Other values (3) 384
 
4.8%

소재지지번주소
Text

Distinct651
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-21T03:34:16.804837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length20.747706
Min length11

Characters and Unicode

Total characters13569
Distinct characters233
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

Unique648 ?
Unique (%)99.1%

Sample

1st row경기도 고양시 일산서구 가좌동 1100번지
2nd row경기도 파주시 금릉동 449번지
3rd row경기도 시흥시 논곡동 160-45번지
4th row경기도 안산시 단원구 고잔동 431-4번지
5th row경기도 파주시 동패동 1744번지
ValueCountFrequency (%)
경기도 654
 
21.4%
수원시 57
 
1.9%
용인시 50
 
1.6%
성남시 46
 
1.5%
화성시 45
 
1.5%
고양시 44
 
1.4%
남양주시 36
 
1.2%
부천시 33
 
1.1%
안산시 30
 
1.0%
파주시 28
 
0.9%
Other values (1157) 2028
66.5%
2024-04-21T03:34:17.214664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2400
17.7%
기 680
 
5.0%
지 678
 
5.0%
도 671
 
4.9%
경 655
 
4.8%
시 654
 
4.8%
번 646
 
4.8%
동 550
 
4.1%
1 478
 
3.5%
구 298
 
2.2%
Other values (223) 5859
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8574
63.2%
Space Separator 2400
 
17.7%
Decimal Number 2316
 
17.1%
Dash Punctuation 279
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 680
 
7.9%
지 678
 
7.9%
도 671
 
7.8%
경 655
 
7.6%
시 654
 
7.6%
번 646
 
7.5%
동 550
 
6.4%
구 298
 
3.5%
양 185
 
2.2%
리 168
 
2.0%
Other values (211) 3389
39.5%
Decimal Number
ValueCountFrequency (%)
1 478
20.6%
2 263
11.4%
5 243
10.5%
3 225
9.7%
4 207
8.9%
6 207
8.9%
7 197
8.5%
8 179
 
7.7%
0 168
 
7.3%
9 149
 
6.4%
Space Separator
ValueCountFrequency (%)
2400
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8574
63.2%
Common 4995
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 680
 
7.9%
지 678
 
7.9%
도 671
 
7.8%
경 655
 
7.6%
시 654
 
7.6%
번 646
 
7.5%
동 550
 
6.4%
구 298
 
3.5%
양 185
 
2.2%
리 168
 
2.0%
Other values (211) 3389
39.5%
Common
ValueCountFrequency (%)
2400
48.0%
1 478
 
9.6%
- 279
 
5.6%
2 263
 
5.3%
5 243
 
4.9%
3 225
 
4.5%
4 207
 
4.1%
6 207
 
4.1%
7 197
 
3.9%
8 179
 
3.6%
Other values (2) 317
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8574
63.2%
ASCII 4995
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2400
48.0%
1 478
 
9.6%
- 279
 
5.6%
2 263
 
5.3%
5 243
 
4.9%
3 225
 
4.5%
4 207
 
4.1%
6 207
 
4.1%
7 197
 
3.9%
8 179
 
3.6%
Other values (2) 317
 
6.3%
Hangul
ValueCountFrequency (%)
기 680
 
7.9%
지 678
 
7.9%
도 671
 
7.8%
경 655
 
7.6%
시 654
 
7.6%
번 646
 
7.5%
동 550
 
6.4%
구 298
 
3.5%
양 185
 
2.2%
리 168
 
2.0%
Other values (211) 3389
39.5%

소재지도로명주소
Text

MISSING 

Distinct644
Distinct (%)99.5%
Missing7
Missing (%)1.1%
Memory size5.2 KiB
2024-04-21T03:34:17.478238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length19.374034
Min length13

Characters and Unicode

Total characters12535
Distinct characters287
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

Unique641 ?
Unique (%)99.1%

Sample

1st row경기도 고양시 일산서구 가좌2로 15
2nd row경기도 파주시 쇠재1길 21
3rd row경기도 시흥시 수인로2421번길 72
4th row경기도 안산시 단원구 단원로 27
5th row경기도 파주시 책향기숲길 39
ValueCountFrequency (%)
경기도 647
 
21.4%
수원시 57
 
1.9%
용인시 49
 
1.6%
성남시 46
 
1.5%
화성시 45
 
1.5%
고양시 41
 
1.4%
남양주시 35
 
1.2%
부천시 33
 
1.1%
안산시 30
 
1.0%
파주시 28
 
0.9%
Other values (1049) 2016
66.6%
2024-04-21T03:34:17.854352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2380
19.0%
기 676
 
5.4%
도 668
 
5.3%
경 661
 
5.3%
시 654
 
5.2%
로 587
 
4.7%
1 444
 
3.5%
구 297
 
2.4%
2 296
 
2.4%
3 249
 
2.0%
Other values (277) 5623
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7914
63.1%
Space Separator 2380
 
19.0%
Decimal Number 2160
 
17.2%
Dash Punctuation 81
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 676
 
8.5%
도 668
 
8.4%
경 661
 
8.4%
시 654
 
8.3%
로 587
 
7.4%
구 297
 
3.8%
길 245
 
3.1%
양 180
 
2.3%
번 166
 
2.1%
안 137
 
1.7%
Other values (265) 3643
46.0%
Decimal Number
ValueCountFrequency (%)
1 444
20.6%
2 296
13.7%
3 249
11.5%
5 220
10.2%
4 209
9.7%
7 176
 
8.1%
6 155
 
7.2%
8 151
 
7.0%
9 130
 
6.0%
0 130
 
6.0%
Space Separator
ValueCountFrequency (%)
2380
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7914
63.1%
Common 4621
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 676
 
8.5%
도 668
 
8.4%
경 661
 
8.4%
시 654
 
8.3%
로 587
 
7.4%
구 297
 
3.8%
길 245
 
3.1%
양 180
 
2.3%
번 166
 
2.1%
안 137
 
1.7%
Other values (265) 3643
46.0%
Common
ValueCountFrequency (%)
2380
51.5%
1 444
 
9.6%
2 296
 
6.4%
3 249
 
5.4%
5 220
 
4.8%
4 209
 
4.5%
7 176
 
3.8%
6 155
 
3.4%
8 151
 
3.3%
9 130
 
2.8%
Other values (2) 211
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7914
63.1%
ASCII 4621
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2380
51.5%
1 444
 
9.6%
2 296
 
6.4%
3 249
 
5.4%
5 220
 
4.8%
4 209
 
4.5%
7 176
 
3.8%
6 155
 
3.4%
8 151
 
3.3%
9 130
 
2.8%
Other values (2) 211
 
4.6%
Hangul
ValueCountFrequency (%)
기 676
 
8.5%
도 668
 
8.4%
경 661
 
8.4%
시 654
 
8.3%
로 587
 
7.4%
구 297
 
3.8%
길 245
 
3.1%
양 180
 
2.3%
번 166
 
2.1%
안 137
 
1.7%
Other values (265) 3643
46.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct626
Distinct (%)96.8%
Missing7
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean14292.334
Minimum10011
Maximum18632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T03:34:17.974288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10306.3
Q112037.5
median14296
Q316682
95-th percentile18389.9
Maximum18632
Range8621
Interquartile range (IQR)4644.5

Descriptive statistics

Standard deviation2624.5605
Coefficient of variation (CV)0.18363414
Kurtosis-1.2850625
Mean14292.334
Median Absolute Deviation (MAD)2340
Skewness-0.0014610381
Sum9247140
Variance6888317.8
MonotonicityNot monotonic
2024-04-21T03:34:18.079985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13370 3
 
0.5%
10826 2
 
0.3%
15819 2
 
0.3%
14485 2
 
0.3%
11618 2
 
0.3%
13183 2
 
0.3%
12901 2
 
0.3%
16254 2
 
0.3%
17888 2
 
0.3%
14106 2
 
0.3%
Other values (616) 626
95.7%
(Missing) 7
 
1.1%
ValueCountFrequency (%)
10011 1
0.2%
10024 1
0.2%
10031 1
0.2%
10032 1
0.2%
10039 1
0.2%
10056 1
0.2%
10057 1
0.2%
10068 1
0.2%
10070 1
0.2%
10071 1
0.2%
ValueCountFrequency (%)
18632 1
0.2%
18611 1
0.2%
18601 1
0.2%
18592 1
0.2%
18587 1
0.2%
18585 1
0.2%
18569 1
0.2%
18564 1
0.2%
18555 1
0.2%
18550 1
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct644
Distinct (%)99.5%
Missing7
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean37.440302
Minimum36.944873
Maximum38.183026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T03:34:18.190504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.944873
5-th percentile37.070703
Q137.281165
median37.391633
Q337.629249
95-th percentile37.840431
Maximum38.183026
Range1.2381526
Interquartile range (IQR)0.34808396

Descriptive statistics

Standard deviation0.233729
Coefficient of variation (CV)0.0062427115
Kurtosis-0.2236657
Mean37.440302
Median Absolute Deviation (MAD)0.14728876
Skewness0.39339028
Sum24223.875
Variance0.054629248
MonotonicityNot monotonic
2024-04-21T03:34:18.309869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.9978850245 2
 
0.3%
37.48075804 2
 
0.3%
37.7468240687 2
 
0.3%
37.3669099197 1
 
0.2%
37.34634422 1
 
0.2%
37.3033653056 1
 
0.2%
37.286086206 1
 
0.2%
37.3183183969 1
 
0.2%
37.300266966 1
 
0.2%
37.2618836817 1
 
0.2%
Other values (634) 634
96.9%
(Missing) 7
 
1.1%
ValueCountFrequency (%)
36.9448733701 1
0.2%
36.9624861144 1
0.2%
36.9819895507 1
0.2%
36.9823816543 1
0.2%
36.984151094 1
0.2%
36.9856264456 1
0.2%
36.9861031214 1
0.2%
36.9892683743 1
0.2%
36.9930049122 1
0.2%
36.9977497254 1
0.2%
ValueCountFrequency (%)
38.1830259643 1
0.2%
38.1580445835 1
0.2%
38.1070784001 1
0.2%
38.0936402007 1
0.2%
38.0669048575 1
0.2%
38.0348374997 1
0.2%
38.0343050876 1
0.2%
38.0306216926 1
0.2%
38.0267036934 1
0.2%
38.00004072 1
0.2%

WGS84경도
Real number (ℝ)

MISSING 

Distinct644
Distinct (%)99.5%
Missing7
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean127.02862
Minimum126.55297
Maximum127.75564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T03:34:18.426561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55297
5-th percentile126.73125
Q1126.84743
median127.04716
Q3127.1437
95-th percentile127.47338
Maximum127.75564
Range1.2026783
Interquartile range (IQR)0.29626627

Descriptive statistics

Standard deviation0.21774824
Coefficient of variation (CV)0.0017141668
Kurtosis0.44336781
Mean127.02862
Median Absolute Deviation (MAD)0.14097502
Skewness0.60882107
Sum82187.517
Variance0.047414296
MonotonicityNot monotonic
2024-04-21T03:34:18.568278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0960046328 2
 
0.3%
126.8101604604 2
 
0.3%
127.0236699068 2
 
0.3%
126.9637315123 1
 
0.2%
127.1236016346 1
 
0.2%
126.9663382816 1
 
0.2%
126.9826940588 1
 
0.2%
126.9823716611 1
 
0.2%
126.9810736937 1
 
0.2%
127.0780995675 1
 
0.2%
Other values (634) 634
96.9%
(Missing) 7
 
1.1%
ValueCountFrequency (%)
126.5529658366 1
0.2%
126.5790592929 1
0.2%
126.5837243594 1
0.2%
126.5950026619 1
0.2%
126.6021470662 1
0.2%
126.6234555631 1
0.2%
126.625148905 1
0.2%
126.6257866929 1
0.2%
126.628434032 1
0.2%
126.6356423571 1
0.2%
ValueCountFrequency (%)
127.7556441846 1
0.2%
127.71245331 1
0.2%
127.7114410955 1
0.2%
127.6834954453 1
0.2%
127.6725007287 1
0.2%
127.6632603774 1
0.2%
127.6462926202 1
0.2%
127.6354555731 1
0.2%
127.6328718845 1
0.2%
127.6209535771 1
0.2%

Interactions

2024-04-21T03:34:14.782399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.168734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.524748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.875452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.332532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.600134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.981086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.436866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:14.679510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:34:18.648267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명소재지우편번호WGS84위도WGS84경도
설립구분명1.0000.1820.2680.258
소재지우편번호0.1821.0000.9100.836
WGS84위도0.2680.9101.0000.564
WGS84경도0.2580.8360.5641.000
2024-04-21T03:34:18.728118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도설립구분명
소재지우편번호1.000-0.9190.1660.139
WGS84위도-0.9191.000-0.1720.204
WGS84경도0.166-0.1721.0000.197
설립구분명0.1390.2040.1971.000

Missing values

2024-04-21T03:34:15.089324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:34:15.188772image/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.
2024-04-21T03:34:15.281821image/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

설립구분명시설명전화번호소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
0공립고양송산중학교031-910-1319경기도 고양시 일산서구 가좌동 1100번지경기도 고양시 일산서구 가좌2로 151021037.68786126.722061
1공립금촌중학교031-940-2311경기도 파주시 금릉동 449번지경기도 파주시 쇠재1길 211093437.751276126.778813
2공립논곡중학교070-7097-1390경기도 시흥시 논곡동 160-45번지경기도 시흥시 수인로2421번길 721498437.388868126.857218
3공립단원중학교070-5202-2206경기도 안산시 단원구 고잔동 431-4번지경기도 안산시 단원구 단원로 271533437.327888126.822803
4공립두일중학교031-940-6900경기도 파주시 동패동 1744번지경기도 파주시 책향기숲길 391088537.719919126.71241
5공립비룡중학교031-678-9340경기도 안성시 당왕동 536-1번지경기도 안성시 남파로 1161757037.015715127.262708
6공립서호중학교031-293-5207경기도 수원시 권선구 서둔동 103-22번지경기도 수원시 권선구 서호로 711661437.266323126.987859
7공립석수중학교070-4322-0975경기도 안산시 단원구 선부동 646-1번지경기도 안산시 단원구 선부로 1331521137.342917126.80929
8공립용천중학교031-323-6214경기도 용인시 처인구 이동읍 천리 1132번지경기도 용인시 처인구 이동읍 백옥대로587번길 541712937.191335127.200978
9공립임곡중학교031-8084-4100경기도 안양시 동안구 비산동 511-129번지경기도 안양시 동안구 임곡로 1051391637.408601126.93157
설립구분명시설명전화번호소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
644공립용인백현중학교031-693-8011경기도 용인시 기흥구 동백7로 107번길<NA><NA><NA><NA>
645공립송내중앙중학교031-859-6315~8경기도 동두천시 송내동 665번지경기도 동두천시 중앙로 781135137.888353127.052533
646공립광주광남중학교031-798-6771경기도 광주시 태전동 131-6번지경기도 광주시 벼루개길42번길 501278937.380505127.236318
647공립도곡중학교031-686-8565경기도 평택시 포승읍 도곡리 1112번지경기도 평택시 포승읍 여술로 581795436.989268126.848808
648공립세종중학교031-884-6175경기도 여주시 교동 121-11번지경기도 여주시 세종로 204-171265037.279525127.632872
649공립신평중학교031-796-2195,2182경기도 하남시 신장동 214-3번지경기도 하남시 신장동로 571294837.544034127.214201
650공립월곶중학교070-7158-9000경기도 시흥시 월곶동 1010-2번지경기도 시흥시 월곶해안로 631496537.392658126.737944
651공립이충중학교031-615-3700경기도 평택시 이충동 675번지경기도 평택시 이충로35번길 51773637.05952127.068976
652공립판곡중학교031-593-8436경기도 남양주시 호평동 456-3번지경기도 남양주시 늘을1로 1151214237.662797127.241865
653공립서정중학교031-970-1691경기도 고양시 덕양구 행신동 1070번지경기도 고양시 덕양구 서정마을로 221049137.618429126.849785