Overview

Dataset statistics

Number of variables8
Number of observations485
Missing cells12
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.9 KiB
Average record size in memory67.3 B

Variable types

Categorical1
Text4
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
시설명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:34:53.526328
Analysis finished2024-04-20 18:34:56.088018
Duration2.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설립구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
공립
349 
사립
136 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 349
72.0%
사립 136
 
28.0%

Length

2024-04-21T03:34:56.138809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:34:56.211892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 349
72.0%
사립 136
 
28.0%

시설명
Text

UNIQUE 

Distinct485
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-21T03:34:56.379735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length6
Mean length6.857732
Min length6

Characters and Unicode

Total characters3326
Distinct characters250
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique485 ?
Unique (%)100.0%

Sample

1st row원종고등학교
2nd row유신고등학교
3rd row율곡고등학교
4th row율면고등학교
5th row은행고등학교
ValueCountFrequency (%)
원종고등학교 1
 
0.2%
주엽고등학교 1
 
0.2%
청학고등학교 1
 
0.2%
청운고등학교 1
 
0.2%
청명고등학교 1
 
0.2%
청담고등학교 1
 
0.2%
창현고등학교 1
 
0.2%
경기관광고등학교 1
 
0.2%
동탄국제고등학교 1
 
0.2%
저현고등학교 1
 
0.2%
Other values (476) 476
97.9%
2024-04-21T03:34:56.721168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 503
15.1%
고 495
14.9%
교 491
14.8%
등 485
14.6%
양 33
 
1.0%
경 33
 
1.0%
원 31
 
0.9%
동 30
 
0.9%
산 29
 
0.9%
자 29
 
0.9%
Other values (240) 1167
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3307
99.4%
Lowercase Letter 14
 
0.4%
Uppercase Letter 4
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 503
15.2%
고 495
15.0%
교 491
14.8%
등 485
14.7%
양 33
 
1.0%
경 33
 
1.0%
원 31
 
0.9%
동 30
 
0.9%
산 29
 
0.9%
자 29
 
0.9%
Other values (227) 1148
34.7%
Lowercase Letter
ValueCountFrequency (%)
s 4
28.6%
i 2
14.3%
n 2
14.3%
e 2
14.3%
u 1
 
7.1%
h 1
 
7.1%
l 1
 
7.1%
g 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
I 1
25.0%
B 1
25.0%
E 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3307
99.4%
Latin 18
 
0.5%
Common 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 503
15.2%
고 495
15.0%
교 491
14.8%
등 485
14.7%
양 33
 
1.0%
경 33
 
1.0%
원 31
 
0.9%
동 30
 
0.9%
산 29
 
0.9%
자 29
 
0.9%
Other values (227) 1148
34.7%
Latin
ValueCountFrequency (%)
s 4
22.2%
i 2
11.1%
n 2
11.1%
e 2
11.1%
T 1
 
5.6%
I 1
 
5.6%
u 1
 
5.6%
B 1
 
5.6%
h 1
 
5.6%
l 1
 
5.6%
Other values (2) 2
11.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3307
99.4%
ASCII 19
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 503
15.2%
고 495
15.0%
교 491
14.8%
등 485
14.7%
양 33
 
1.0%
경 33
 
1.0%
원 31
 
0.9%
동 30
 
0.9%
산 29
 
0.9%
자 29
 
0.9%
Other values (227) 1148
34.7%
ASCII
ValueCountFrequency (%)
s 4
21.1%
i 2
10.5%
n 2
10.5%
e 2
10.5%
T 1
 
5.3%
I 1
 
5.3%
u 1
 
5.3%
B 1
 
5.3%
1
 
5.3%
h 1
 
5.3%
Other values (3) 3
15.8%

전화번호
Text

UNIQUE 

Distinct485
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-21T03:34:56.934011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.115464
Min length10

Characters and Unicode

Total characters5876
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique485 ?
Unique (%)100.0%

Sample

1st row032-222-5807
2nd row031-547-4500
3rd row031-958-0832
4th row031-641-0664
5th row031-363-5000
ValueCountFrequency (%)
032-222-5807 1
 
0.2%
032-340-6102 1
 
0.2%
031-412-8492 1
 
0.2%
031-821-3235 1
 
0.2%
031-771-7931 1
 
0.2%
031-201-9600 1
 
0.2%
031-691-8095 1
 
0.2%
031-548-5000~1 1
 
0.2%
031-882-9196 1
 
0.2%
031-8015-9000 1
 
0.2%
Other values (475) 475
97.9%
2024-04-21T03:34:57.254612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1224
20.8%
- 964
16.4%
3 772
13.1%
1 763
13.0%
2 381
 
6.5%
8 338
 
5.8%
5 312
 
5.3%
9 291
 
5.0%
6 290
 
4.9%
7 285
 
4.9%
Other values (5) 256
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4906
83.5%
Dash Punctuation 964
 
16.4%
Other Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1224
24.9%
3 772
15.7%
1 763
15.6%
2 381
 
7.8%
8 338
 
6.9%
5 312
 
6.4%
9 291
 
5.9%
6 290
 
5.9%
7 285
 
5.8%
4 250
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 964
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5876
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1224
20.8%
- 964
16.4%
3 772
13.1%
1 763
13.0%
2 381
 
6.5%
8 338
 
5.8%
5 312
 
5.3%
9 291
 
5.0%
6 290
 
4.9%
7 285
 
4.9%
Other values (5) 256
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1224
20.8%
- 964
16.4%
3 772
13.1%
1 763
13.0%
2 381
 
6.5%
8 338
 
5.8%
5 312
 
5.3%
9 291
 
5.0%
6 290
 
4.9%
7 285
 
4.9%
Other values (5) 256
 
4.4%

소재지지번주소
Text

Distinct473
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-21T03:34:57.458958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length20.748454
Min length15

Characters and Unicode

Total characters10063
Distinct characters209
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

Unique462 ?
Unique (%)95.3%

Sample

1st row경기도 부천시 오정구 원종동 128-1번지
2nd row경기도 수원시 팔달구 우만동 9-1번지
3rd row경기도 파주시 법원읍 법원리 447-47번지
4th row경기도 이천시 율면 고당리 545번지
5th row경기도 시흥시 은행동 543-2번지
ValueCountFrequency (%)
경기도 485
 
21.5%
수원시 44
 
1.9%
고양시 38
 
1.7%
성남시 36
 
1.6%
용인시 32
 
1.4%
화성시 29
 
1.3%
부천시 28
 
1.2%
안산시 24
 
1.1%
분당구 24
 
1.1%
안양시 21
 
0.9%
Other values (875) 1498
66.3%
2024-04-21T03:34:57.771831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1775
17.6%
지 504
 
5.0%
기 501
 
5.0%
도 493
 
4.9%
시 487
 
4.8%
경 485
 
4.8%
번 483
 
4.8%
동 433
 
4.3%
1 357
 
3.5%
구 233
 
2.3%
Other values (199) 4312
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6360
63.2%
Space Separator 1775
 
17.6%
Decimal Number 1715
 
17.0%
Dash Punctuation 213
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 504
 
7.9%
기 501
 
7.9%
도 493
 
7.8%
시 487
 
7.7%
경 485
 
7.6%
번 483
 
7.6%
동 433
 
6.8%
구 233
 
3.7%
양 146
 
2.3%
산 109
 
1.7%
Other values (187) 2486
39.1%
Decimal Number
ValueCountFrequency (%)
1 357
20.8%
2 179
10.4%
5 178
10.4%
4 164
9.6%
6 160
9.3%
3 157
9.2%
8 143
8.3%
7 136
 
7.9%
0 131
 
7.6%
9 110
 
6.4%
Space Separator
ValueCountFrequency (%)
1775
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6360
63.2%
Common 3703
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 504
 
7.9%
기 501
 
7.9%
도 493
 
7.8%
시 487
 
7.7%
경 485
 
7.6%
번 483
 
7.6%
동 433
 
6.8%
구 233
 
3.7%
양 146
 
2.3%
산 109
 
1.7%
Other values (187) 2486
39.1%
Common
ValueCountFrequency (%)
1775
47.9%
1 357
 
9.6%
- 213
 
5.8%
2 179
 
4.8%
5 178
 
4.8%
4 164
 
4.4%
6 160
 
4.3%
3 157
 
4.2%
8 143
 
3.9%
7 136
 
3.7%
Other values (2) 241
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6360
63.2%
ASCII 3703
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1775
47.9%
1 357
 
9.6%
- 213
 
5.8%
2 179
 
4.8%
5 178
 
4.8%
4 164
 
4.4%
6 160
 
4.3%
3 157
 
4.2%
8 143
 
3.9%
7 136
 
3.7%
Other values (2) 241
 
6.5%
Hangul
ValueCountFrequency (%)
지 504
 
7.9%
기 501
 
7.9%
도 493
 
7.8%
시 487
 
7.7%
경 485
 
7.6%
번 483
 
7.6%
동 433
 
6.8%
구 233
 
3.7%
양 146
 
2.3%
산 109
 
1.7%
Other values (187) 2486
39.1%

소재지도로명주소
Text

Distinct473
Distinct (%)98.1%
Missing3
Missing (%)0.6%
Memory size3.9 KiB
2024-04-21T03:34:57.993438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length19.147303
Min length14

Characters and Unicode

Total characters9229
Distinct characters274
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

Unique465 ?
Unique (%)96.5%

Sample

1st row경기도 부천시 오정구 소사로807번길 68
2nd row경기도 수원시 팔달구 월드컵로 216
3rd row경기도 파주시 법원읍 사임당로 905
4th row경기도 이천시 율면 고당로 48
5th row경기도 시흥시 은행고길 85
ValueCountFrequency (%)
경기도 482
 
21.5%
수원시 44
 
2.0%
고양시 38
 
1.7%
성남시 36
 
1.6%
용인시 32
 
1.4%
화성시 28
 
1.2%
부천시 27
 
1.2%
안산시 24
 
1.1%
분당구 24
 
1.1%
안양시 21
 
0.9%
Other values (801) 1488
66.3%
2024-04-21T03:34:58.318460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1762
19.1%
기 501
 
5.4%
도 495
 
5.4%
시 494
 
5.4%
경 492
 
5.3%
로 451
 
4.9%
1 324
 
3.5%
2 233
 
2.5%
구 231
 
2.5%
3 189
 
2.0%
Other values (264) 4057
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5816
63.0%
Space Separator 1762
 
19.1%
Decimal Number 1596
 
17.3%
Dash Punctuation 55
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 501
 
8.6%
도 495
 
8.5%
시 494
 
8.5%
경 492
 
8.5%
로 451
 
7.8%
구 231
 
4.0%
길 158
 
2.7%
양 134
 
2.3%
안 113
 
1.9%
번 112
 
1.9%
Other values (252) 2635
45.3%
Decimal Number
ValueCountFrequency (%)
1 324
20.3%
2 233
14.6%
3 189
11.8%
5 154
9.6%
6 136
8.5%
4 135
8.5%
7 124
 
7.8%
0 113
 
7.1%
8 95
 
6.0%
9 93
 
5.8%
Space Separator
ValueCountFrequency (%)
1762
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5816
63.0%
Common 3413
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 501
 
8.6%
도 495
 
8.5%
시 494
 
8.5%
경 492
 
8.5%
로 451
 
7.8%
구 231
 
4.0%
길 158
 
2.7%
양 134
 
2.3%
안 113
 
1.9%
번 112
 
1.9%
Other values (252) 2635
45.3%
Common
ValueCountFrequency (%)
1762
51.6%
1 324
 
9.5%
2 233
 
6.8%
3 189
 
5.5%
5 154
 
4.5%
6 136
 
4.0%
4 135
 
4.0%
7 124
 
3.6%
0 113
 
3.3%
8 95
 
2.8%
Other values (2) 148
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5816
63.0%
ASCII 3413
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1762
51.6%
1 324
 
9.5%
2 233
 
6.8%
3 189
 
5.5%
5 154
 
4.5%
6 136
 
4.0%
4 135
 
4.0%
7 124
 
3.6%
0 113
 
3.3%
8 95
 
2.8%
Other values (2) 148
 
4.3%
Hangul
ValueCountFrequency (%)
기 501
 
8.6%
도 495
 
8.5%
시 494
 
8.5%
경 492
 
8.5%
로 451
 
7.8%
구 231
 
4.0%
길 158
 
2.7%
양 134
 
2.3%
안 113
 
1.9%
번 112
 
1.9%
Other values (252) 2635
45.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct455
Distinct (%)94.4%
Missing3
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean14291.139
Minimum10011
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-21T03:34:58.434539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10305.8
Q112104.25
median14282
Q316555.5
95-th percentile18314.4
Maximum18611
Range8600
Interquartile range (IQR)4451.25

Descriptive statistics

Standard deviation2580.634
Coefficient of variation (CV)0.18057581
Kurtosis-1.2254904
Mean14291.139
Median Absolute Deviation (MAD)2254
Skewness-0.018083997
Sum6888329
Variance6659672.1
MonotonicityNot monotonic
2024-04-21T03:34:58.551694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13370 4
 
0.8%
16254 3
 
0.6%
11618 3
 
0.6%
12741 3
 
0.6%
11176 2
 
0.4%
13805 2
 
0.4%
18119 2
 
0.4%
14011 2
 
0.4%
14747 2
 
0.4%
16208 2
 
0.4%
Other values (445) 457
94.2%
(Missing) 3
 
0.6%
ValueCountFrequency (%)
10011 1
0.2%
10023 1
0.2%
10031 1
0.2%
10032 1
0.2%
10057 1
0.2%
10067 1
0.2%
10073 1
0.2%
10077 1
0.2%
10087 1
0.2%
10106 1
0.2%
ValueCountFrequency (%)
18611 1
0.2%
18600 1
0.2%
18599 1
0.2%
18592 1
0.2%
18587 1
0.2%
18569 1
0.2%
18564 1
0.2%
18550 1
0.2%
18506 1
0.2%
18496 1
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct473
Distinct (%)98.1%
Missing3
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean37.43587
Minimum36.962213
Maximum38.158045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-21T03:34:58.658091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.962213
5-th percentile37.066684
Q137.285504
median37.394981
Q337.623288
95-th percentile37.826818
Maximum38.158045
Range1.1958313
Interquartile range (IQR)0.33778395

Descriptive statistics

Standard deviation0.22721231
Coefficient of variation (CV)0.0060693742
Kurtosis-0.25390769
Mean37.43587
Median Absolute Deviation (MAD)0.13806401
Skewness0.31550359
Sum18044.089
Variance0.051625432
MonotonicityNot monotonic
2024-04-21T03:34:58.774189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7468240687 3
 
0.6%
37.395763889 2
 
0.4%
37.4750192648 2
 
0.4%
37.4201701325 2
 
0.4%
37.3190951437 2
 
0.4%
36.9978850245 2
 
0.4%
37.6973374489 2
 
0.4%
37.432610706 2
 
0.4%
37.1883641399 1
 
0.2%
37.4004932431 1
 
0.2%
Other values (463) 463
95.5%
(Missing) 3
 
0.6%
ValueCountFrequency (%)
36.9622132473 1
0.2%
36.9788148435 1
0.2%
36.9856264456 1
0.2%
36.9869167864 1
0.2%
36.9888801443 1
0.2%
36.9897593056 1
0.2%
36.9923237998 1
0.2%
36.9942934574 1
0.2%
36.9967051805 1
0.2%
36.9978850245 2
0.4%
ValueCountFrequency (%)
38.1580445835 1
0.2%
38.1070784001 1
0.2%
38.0860668544 1
0.2%
38.0352260528 1
0.2%
37.960629321 1
0.2%
37.9543167349 1
0.2%
37.945570416 1
0.2%
37.93107436 1
0.2%
37.9119898795 1
0.2%
37.9060470638 1
0.2%

WGS84경도
Real number (ℝ)

Distinct473
Distinct (%)98.1%
Missing3
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean127.02223
Minimum126.56755
Maximum127.75564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-21T03:34:58.897829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56755
5-th percentile126.74219
Q1126.84902
median127.03425
Q3127.13133
95-th percentile127.45726
Maximum127.75564
Range1.1880989
Interquartile range (IQR)0.28231474

Descriptive statistics

Standard deviation0.21398159
Coefficient of variation (CV)0.0016845995
Kurtosis0.67897476
Mean127.02223
Median Absolute Deviation (MAD)0.13444194
Skewness0.71189397
Sum61224.717
Variance0.045788123
MonotonicityNot monotonic
2024-04-21T03:34:59.040000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0236699068 3
 
0.6%
126.9090938926 2
 
0.4%
126.7730502151 2
 
0.4%
127.2639238617 2
 
0.4%
126.9827274923 2
 
0.4%
127.0960046328 2
 
0.4%
126.7421866743 2
 
0.4%
126.9880849893 2
 
0.4%
127.0777653134 1
 
0.2%
126.9013625827 1
 
0.2%
Other values (463) 463
95.5%
(Missing) 3
 
0.6%
ValueCountFrequency (%)
126.5675452515 1
0.2%
126.5790592929 1
0.2%
126.5936583562 1
0.2%
126.6021470662 1
0.2%
126.625148905 1
0.2%
126.628434032 1
0.2%
126.6362623485 1
0.2%
126.6682443582 1
0.2%
126.6773730447 1
0.2%
126.6898276361 1
0.2%
ValueCountFrequency (%)
127.7556441846 1
0.2%
127.7114410955 1
0.2%
127.6834954453 1
0.2%
127.6632603774 1
0.2%
127.6462926202 1
0.2%
127.6354555731 1
0.2%
127.6326893093 1
0.2%
127.6194846592 1
0.2%
127.6184989599 1
0.2%
127.608118886 1
0.2%

Interactions

2024-04-21T03:34:55.591962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.114107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.367555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.660091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.225255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.435037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.750160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.297219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:34:55.511592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:34:59.117753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명소재지우편번호WGS84위도WGS84경도
설립구분명1.0000.1580.2800.194
소재지우편번호0.1581.0000.9120.840
WGS84위도0.2800.9121.0000.551
WGS84경도0.1940.8400.5511.000
2024-04-21T03:34:59.201482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도설립구분명
소재지우편번호1.000-0.9200.1880.121
WGS84위도-0.9201.000-0.2220.213
WGS84경도0.188-0.2221.0000.147
설립구분명0.1210.2130.1471.000

Missing values

2024-04-21T03:34:55.848494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:34:55.950516image/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.
2024-04-21T03:34:56.039504image/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
0공립원종고등학교032-222-5807경기도 부천시 오정구 원종동 128-1번지경기도 부천시 오정구 소사로807번길 681442637.5285126.800497
1사립유신고등학교031-547-4500경기도 수원시 팔달구 우만동 9-1번지경기도 수원시 팔달구 월드컵로 2161649537.282488127.041266
2사립율곡고등학교031-958-0832경기도 파주시 법원읍 법원리 447-47번지경기도 파주시 법원읍 사임당로 9051082637.847993126.881305
3공립율면고등학교031-641-0664경기도 이천시 율면 고당리 545번지경기도 이천시 율면 고당로 481742337.087699127.54251
4공립은행고등학교031-363-5000경기도 시흥시 은행동 543-2번지경기도 시흥시 은행고길 851491637.443436126.80294
5사립은혜고등학교031-615-2500경기도 평택시 장안동 389-1번지경기도 평택시 장안웃길 661773137.066542127.081647
6공립의정부고등학교031-874-2996경기도 의정부시 가능동 359-3번지경기도 의정부시 녹양로 291161737.754921127.031269
7공립의정부여자고등학교031-876-4201경기도 의정부시 가능동 653번지경기도 의정부시 신흥로365번길 101167937.750075127.041232
8공립이매고등학교031-704-4042경기도 성남시 분당구 이매동 147번지경기도 성남시 분당구 탄천로 11356537.392912127.121652
9공립이천고등학교031-645-0800경기도 이천시 증포동 402번지경기도 이천시 아리역로16번길 11735337.287971127.447619
설립구분명시설명전화번호소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
475공립처인고등학교031-724-2100경기도 용인시 처인구 남사읍 아곡리 706번지경기도 용인시 처인구 남사읍 한숲로 321711737.151258127.170325
476공립신원고등학교02-3146-8600경기도 고양시 덕양구 신원동 602번지경기도 고양시 덕양구 통일로 3911056737.668399126.886949
477공립이솔고등학교031-899-5911경기도 화성시 동탄대로 7길 10<NA><NA><NA><NA>
478사립용문고등학교031-773-3533경기도 양평군 용문면 마룡리 663-2번지경기도 양평군 용문면 용문로 4371251537.49187127.598835
479공립용인고등학교031-330-8309경기도 용인시 처인구 역북동 444-1번지경기도 용인시 처인구 금학로253번길 20-211704637.240559127.193083
480사립덕영고등학교031-329-4300경기도 용인시 처인구 고림동 737-1번지경기도 용인시 처인구 고림로74번길 151715137.241671127.216045
481공립용호고등학교031-390-4464경기도 군포시 당동 875번지경기도 군포시 용호2로 101587637.341856126.939355
482사립우성고등학교031-3619-200경기도 의왕시 고천동 496번지경기도 의왕시 오전로 371606237.349291126.980669
483공립원곡고등학교031-8085-0008경기도 안산시 단원구 원곡동 965-1번지경기도 안산시 단원구 화랑로 151536437.332858126.798681
484공립원미고등학교032-722-6200경기도 부천시 원미구 중동 1098번지경기도 부천시 원미구 옥산로 481457537.498207126.782736