Overview

Dataset statistics

Number of variables20
Number of observations7065
Missing cells3410
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory166.0 B

Variable types

Text6
Categorical2
DateTime3
Numeric6
Boolean3

Dataset

Description무더위 쉼터 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4FSFNY7BANKX85VT7V9I13311186&infSeq=1

Alerts

특이사항 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
숙박가능여부 is highly overall correlated with 특이사항High correlation
시설면적 is highly overall correlated with 이용가능인원수High correlation
이용가능인원수 is highly overall correlated with 시설면적High correlation
위도 is highly overall correlated with 특이사항High correlation
시설유형 is highly imbalanced (73.3%)Imbalance
숙박가능여부 is highly imbalanced (99.1%)Imbalance
특이사항 is highly imbalanced (64.0%)Imbalance
선풍기보유현황 has 580 (8.2%) missing valuesMissing
에어컨보유현황 has 550 (7.8%) missing valuesMissing
야간개방 has 534 (7.6%) missing valuesMissing
휴일개방 has 534 (7.6%) missing valuesMissing
숙박가능여부 has 534 (7.6%) missing valuesMissing
관리기관전화번호 has 656 (9.3%) missing valuesMissing
시설면적 has 71 (1.0%) zerosZeros
이용가능인원수 has 103 (1.5%) zerosZeros
선풍기보유현황 has 518 (7.3%) zerosZeros

Reproduction

Analysis started2024-03-16 04:30:04.413488
Analysis finished2024-03-16 04:30:24.455679
Duration20.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct6827
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
2024-03-16T04:30:25.128918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length8.861288
Min length2

Characters and Unicode

Total characters62605
Distinct characters565
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6644 ?
Unique (%)94.0%

Sample

1st row읍내10리 경로당
2nd row설악면행정복지센터
3rd row위곡1리 경로당
4th row선촌2리(탐선) 경로당
5th row송산2리 경로당
ValueCountFrequency (%)
경로당 2939
 
25.2%
마을회관 452
 
3.9%
2리 71
 
0.6%
1리 70
 
0.6%
새마을금고 51
 
0.4%
3리 39
 
0.3%
nh농협은행 28
 
0.2%
주민센터 26
 
0.2%
행정복지센터 25
 
0.2%
휴먼시아 16
 
0.1%
Other values (6869) 7923
68.1%
2024-03-16T04:30:26.764353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5541
 
8.9%
5511
 
8.8%
5487
 
8.8%
4603
 
7.4%
2713
 
4.3%
1 1491
 
2.4%
1289
 
2.1%
2 1263
 
2.0%
1234
 
2.0%
( 1176
 
1.9%
Other values (555) 32297
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50685
81.0%
Space Separator 4603
 
7.4%
Decimal Number 4504
 
7.2%
Open Punctuation 1178
 
1.9%
Close Punctuation 1178
 
1.9%
Uppercase Letter 238
 
0.4%
Other Punctuation 151
 
0.2%
Lowercase Letter 37
 
0.1%
Dash Punctuation 30
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5541
 
10.9%
5511
 
10.9%
5487
 
10.8%
2713
 
5.4%
1289
 
2.5%
1234
 
2.4%
1145
 
2.3%
963
 
1.9%
960
 
1.9%
897
 
1.8%
Other values (510) 24945
49.2%
Uppercase Letter
ValueCountFrequency (%)
A 50
21.0%
H 44
18.5%
L 32
13.4%
N 28
11.8%
S 24
10.1%
G 24
10.1%
K 15
 
6.3%
C 10
 
4.2%
T 3
 
1.3%
I 3
 
1.3%
Other values (5) 5
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 1491
33.1%
2 1263
28.0%
3 624
13.9%
4 339
 
7.5%
5 238
 
5.3%
6 164
 
3.6%
7 126
 
2.8%
8 100
 
2.2%
9 84
 
1.9%
0 75
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 69
45.7%
@ 66
43.7%
. 9
 
6.0%
· 3
 
2.0%
" 1
 
0.7%
/ 1
 
0.7%
? 1
 
0.7%
& 1
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
e 29
78.4%
k 3
 
8.1%
s 2
 
5.4%
c 2
 
5.4%
i 1
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 1176
99.8%
[ 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1176
99.8%
] 2
 
0.2%
Space Separator
ValueCountFrequency (%)
4603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50684
81.0%
Common 11645
 
18.6%
Latin 275
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5541
 
10.9%
5511
 
10.9%
5487
 
10.8%
2713
 
5.4%
1289
 
2.5%
1234
 
2.4%
1145
 
2.3%
963
 
1.9%
960
 
1.9%
897
 
1.8%
Other values (509) 24944
49.2%
Common
ValueCountFrequency (%)
4603
39.5%
1 1491
 
12.8%
2 1263
 
10.8%
( 1176
 
10.1%
) 1176
 
10.1%
3 624
 
5.4%
4 339
 
2.9%
5 238
 
2.0%
6 164
 
1.4%
7 126
 
1.1%
Other values (15) 445
 
3.8%
Latin
ValueCountFrequency (%)
A 50
18.2%
H 44
16.0%
L 32
11.6%
e 29
10.5%
N 28
10.2%
S 24
8.7%
G 24
8.7%
K 15
 
5.5%
C 10
 
3.6%
k 3
 
1.1%
Other values (10) 16
 
5.8%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50684
81.0%
ASCII 11917
 
19.0%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5541
 
10.9%
5511
 
10.9%
5487
 
10.8%
2713
 
5.4%
1289
 
2.5%
1234
 
2.4%
1145
 
2.3%
963
 
1.9%
960
 
1.9%
897
 
1.8%
Other values (509) 24944
49.2%
ASCII
ValueCountFrequency (%)
4603
38.6%
1 1491
 
12.5%
2 1263
 
10.6%
( 1176
 
9.9%
) 1176
 
9.9%
3 624
 
5.2%
4 339
 
2.8%
5 238
 
2.0%
6 164
 
1.4%
7 126
 
1.1%
Other values (34) 717
 
6.0%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct875
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
2024-03-16T04:30:27.767020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length9.5906582
Min length2

Characters and Unicode

Total characters67758
Distinct characters246
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

Unique296 ?
Unique (%)4.2%

Sample

1st row경기도 가평군 가평읍
2nd row경기도 가평군 설악면
3rd row경기도 가평군 설악면
4th row경기도 가평군 설악면
5th row경기도 가평군 설악면
ValueCountFrequency (%)
경기도 4896
26.7%
화성시 700
 
3.8%
안성시 512
 
2.8%
수원시 482
 
2.6%
평택시 457
 
2.5%
이천시 394
 
2.1%
부천시 361
 
2.0%
여주시 309
 
1.7%
양주시 273
 
1.5%
안산시 229
 
1.2%
Other values (890) 9736
53.1%
2024-03-16T04:30:29.434662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11343
16.7%
5272
 
7.8%
5084
 
7.5%
5058
 
7.5%
4883
 
7.2%
4119
 
6.1%
1990
 
2.9%
1648
 
2.4%
1197
 
1.8%
1195
 
1.8%
Other values (236) 25969
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55087
81.3%
Space Separator 11343
 
16.7%
Decimal Number 1257
 
1.9%
Dash Punctuation 71
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5272
 
9.6%
5084
 
9.2%
5058
 
9.2%
4883
 
8.9%
4119
 
7.5%
1990
 
3.6%
1648
 
3.0%
1197
 
2.2%
1195
 
2.2%
1072
 
1.9%
Other values (224) 23569
42.8%
Decimal Number
ValueCountFrequency (%)
1 320
25.5%
2 303
24.1%
3 176
14.0%
6 89
 
7.1%
4 86
 
6.8%
5 83
 
6.6%
7 64
 
5.1%
8 52
 
4.1%
9 42
 
3.3%
0 42
 
3.3%
Space Separator
ValueCountFrequency (%)
11343
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55087
81.3%
Common 12671
 
18.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5272
 
9.6%
5084
 
9.2%
5058
 
9.2%
4883
 
8.9%
4119
 
7.5%
1990
 
3.6%
1648
 
3.0%
1197
 
2.2%
1195
 
2.2%
1072
 
1.9%
Other values (224) 23569
42.8%
Common
ValueCountFrequency (%)
11343
89.5%
1 320
 
2.5%
2 303
 
2.4%
3 176
 
1.4%
6 89
 
0.7%
4 86
 
0.7%
5 83
 
0.7%
- 71
 
0.6%
7 64
 
0.5%
8 52
 
0.4%
Other values (2) 84
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55087
81.3%
ASCII 12671
 
18.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11343
89.5%
1 320
 
2.5%
2 303
 
2.4%
3 176
 
1.4%
6 89
 
0.7%
4 86
 
0.7%
5 83
 
0.7%
- 71
 
0.6%
7 64
 
0.5%
8 52
 
0.4%
Other values (2) 84
 
0.7%
Hangul
ValueCountFrequency (%)
5272
 
9.6%
5084
 
9.2%
5058
 
9.2%
4883
 
8.9%
4119
 
7.5%
1990
 
3.6%
1648
 
3.0%
1197
 
2.2%
1195
 
2.2%
1072
 
1.9%
Other values (224) 23569
42.8%

시설유형
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
노인시설
6087 
마을회관
 
474
주민센터
 
150
금융기관
 
135
기타
 
107
Other values (5)
 
112

Length

Max length6
Median length4
Mean length3.9832979
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노인시설
2nd row읍면동사무소
3rd row노인시설
4th row노인시설
5th row노인시설

Common Values

ValueCountFrequency (%)
노인시설 6087
86.2%
마을회관 474
 
6.7%
주민센터 150
 
2.1%
금융기관 135
 
1.9%
기타 107
 
1.5%
읍면동사무소 58
 
0.8%
복지회관 38
 
0.5%
정자 7
 
0.1%
보건소 6
 
0.1%
종교시설 3
 
< 0.1%

Length

2024-03-16T04:30:30.034559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:30:30.475432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인시설 6087
86.2%
마을회관 474
 
6.7%
주민센터 150
 
2.1%
금융기관 135
 
1.9%
기타 107
 
1.5%
읍면동사무소 58
 
0.8%
복지회관 38
 
0.5%
정자 7
 
0.1%
보건소 6
 
0.1%
종교시설 3
 
< 0.1%
Distinct52
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
Minimum1991-03-19 00:00:00
Maximum2023-08-16 00:00:00
2024-03-16T04:30:31.080829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:31.595099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct18
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
Minimum2017-09-30 00:00:00
Maximum2059-12-31 00:00:00
2024-03-16T04:30:31.929632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:32.365030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

시설면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2543
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.31624
Minimum0
Maximum18384
Zeros71
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:32.791432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile39.6
Q179.9
median109
Q3158
95-th percentile317.8
Maximum18384
Range18384
Interquartile range (IQR)78.1

Descriptive statistics

Standard deviation497.49008
Coefficient of variation (CV)2.8870759
Kurtosis457.49134
Mean172.31624
Median Absolute Deviation (MAD)36.19
Skewness18.047505
Sum1217414.2
Variance247496.38
MonotonicityNot monotonic
2024-03-16T04:30:33.308570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 208
 
2.9%
60.0 119
 
1.7%
132.0 104
 
1.5%
66.0 99
 
1.4%
90.0 98
 
1.4%
100.0 89
 
1.3%
120.0 89
 
1.3%
165.0 73
 
1.0%
0.0 71
 
1.0%
98.0 65
 
0.9%
Other values (2533) 6050
85.6%
ValueCountFrequency (%)
0.0 71
1.0%
4.0 1
 
< 0.1%
7.5 1
 
< 0.1%
10.0 2
 
< 0.1%
12.8 1
 
< 0.1%
13.2 1
 
< 0.1%
14.0 1
 
< 0.1%
14.7 2
 
< 0.1%
15.0 1
 
< 0.1%
16.2 1
 
< 0.1%
ValueCountFrequency (%)
18384.0 1
< 0.1%
14155.0 1
< 0.1%
10947.0 1
< 0.1%
9960.0 1
< 0.1%
8427.0 1
< 0.1%
8344.0 1
< 0.1%
7990.0 1
< 0.1%
7267.0 1
< 0.1%
6638.0 1
< 0.1%
6307.0 1
< 0.1%

이용가능인원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct216
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.915499
Minimum0
Maximum2107
Zeros103
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:33.759601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.2
Q121
median30
Q340
95-th percentile72
Maximum2107
Range2107
Interquartile range (IQR)19

Descriptive statistics

Standard deviation75.579766
Coefficient of variation (CV)1.9421508
Kurtosis313.27056
Mean38.915499
Median Absolute Deviation (MAD)10
Skewness15.593833
Sum274938
Variance5712.301
MonotonicityNot monotonic
2024-03-16T04:30:34.237812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 516
 
7.3%
20 479
 
6.8%
25 350
 
5.0%
24 247
 
3.5%
40 235
 
3.3%
50 215
 
3.0%
26 197
 
2.8%
21 189
 
2.7%
22 188
 
2.7%
15 184
 
2.6%
Other values (206) 4265
60.4%
ValueCountFrequency (%)
0 103
1.5%
2 2
 
< 0.1%
3 4
 
0.1%
4 4
 
0.1%
5 22
 
0.3%
6 20
 
0.3%
7 16
 
0.2%
8 39
 
0.6%
9 44
0.6%
10 100
1.4%
ValueCountFrequency (%)
2107 1
< 0.1%
1998 1
< 0.1%
1817 1
< 0.1%
1659 1
< 0.1%
1576 1
< 0.1%
1509 1
< 0.1%
1264 1
< 0.1%
1256 1
< 0.1%
1124 1
< 0.1%
962 1
< 0.1%

선풍기보유현황
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)0.3%
Missing580
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean2.1942945
Minimum0
Maximum36
Zeros518
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:34.652196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum36
Range36
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.669444
Coefficient of variation (CV)0.76081127
Kurtosis43.560915
Mean2.1942945
Median Absolute Deviation (MAD)1
Skewness3.9884912
Sum14230
Variance2.7870433
MonotonicityNot monotonic
2024-03-16T04:30:35.055052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 2483
35.1%
1 1527
21.6%
3 1088
15.4%
0 518
 
7.3%
4 494
 
7.0%
5 180
 
2.5%
6 71
 
1.0%
7 53
 
0.8%
8 25
 
0.4%
10 17
 
0.2%
Other values (10) 29
 
0.4%
(Missing) 580
 
8.2%
ValueCountFrequency (%)
0 518
 
7.3%
1 1527
21.6%
2 2483
35.1%
3 1088
15.4%
4 494
 
7.0%
5 180
 
2.5%
6 71
 
1.0%
7 53
 
0.8%
8 25
 
0.4%
9 5
 
0.1%
ValueCountFrequency (%)
36 1
 
< 0.1%
20 3
 
< 0.1%
18 5
 
0.1%
16 1
 
< 0.1%
15 2
 
< 0.1%
14 3
 
< 0.1%
13 4
 
0.1%
12 4
 
0.1%
11 1
 
< 0.1%
10 17
0.2%

에어컨보유현황
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)0.5%
Missing550
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean1.5502686
Minimum0
Maximum72
Zeros63
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:35.456156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum72
Range72
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2923525
Coefficient of variation (CV)1.4786808
Kurtosis389.47252
Mean1.5502686
Median Absolute Deviation (MAD)0
Skewness17.172575
Sum10100
Variance5.2548798
MonotonicityNot monotonic
2024-03-16T04:30:35.895303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 4480
63.4%
2 1480
 
20.9%
3 261
 
3.7%
4 96
 
1.4%
0 63
 
0.9%
5 46
 
0.7%
6 22
 
0.3%
8 12
 
0.2%
7 10
 
0.1%
10 9
 
0.1%
Other values (22) 36
 
0.5%
(Missing) 550
 
7.8%
ValueCountFrequency (%)
0 63
 
0.9%
1 4480
63.4%
2 1480
 
20.9%
3 261
 
3.7%
4 96
 
1.4%
5 46
 
0.7%
6 22
 
0.3%
7 10
 
0.1%
8 12
 
0.2%
9 7
 
0.1%
ValueCountFrequency (%)
72 1
< 0.1%
62 1
< 0.1%
54 2
< 0.1%
48 1
< 0.1%
47 1
< 0.1%
41 1
< 0.1%
36 1
< 0.1%
35 1
< 0.1%
33 1
< 0.1%
31 1
< 0.1%

야간개방
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing534
Missing (%)7.6%
Memory size13.9 KiB
False
5486 
True
1045 
(Missing)
 
534
ValueCountFrequency (%)
False 5486
77.7%
True 1045
 
14.8%
(Missing) 534
 
7.6%
2024-03-16T04:30:36.252175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

휴일개방
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing534
Missing (%)7.6%
Memory size13.9 KiB
True
3635 
False
2896 
(Missing)
534 
ValueCountFrequency (%)
True 3635
51.5%
False 2896
41.0%
(Missing) 534
 
7.6%
2024-03-16T04:30:36.522527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

숙박가능여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing534
Missing (%)7.6%
Memory size13.9 KiB
False
6526 
True
 
5
(Missing)
 
534
ValueCountFrequency (%)
False 6526
92.4%
True 5
 
0.1%
(Missing) 534
 
7.6%
2024-03-16T04:30:36.763927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

특이사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
<NA>
4997 
없음
868 
N
700 
코로나19로인한 운영중단
 
273
 
160
Other values (11)
 
67

Length

Max length45
Median length4
Mean length3.8093418
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4997
70.7%
없음 868
 
12.3%
N 700
 
9.9%
코로나19로인한 운영중단 273
 
3.9%
160
 
2.3%
경기도 양주시 백석읍 46
 
0.7%
공원 내 정자 8
 
0.1%
코로나19로 인한 미운영 4
 
0.1%
매주 월요일 휴관 2
 
< 0.1%
매주 금요일 휴관+2021년 1월 31일까지 리모델링으로 인한 휴관 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2024-03-16T04:30:37.191262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4997
66.8%
없음 868
 
11.6%
n 700
 
9.4%
코로나19로인한 274
 
3.7%
운영중단 273
 
3.6%
160
 
2.1%
경기도 47
 
0.6%
양주시 47
 
0.6%
백석읍 46
 
0.6%
정자 8
 
0.1%
Other values (23) 63
 
0.8%
Distinct6864
Distinct (%)97.3%
Missing13
Missing (%)0.2%
Memory size55.3 KiB
2024-03-16T04:30:37.897743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length53
Mean length21.553602
Min length12

Characters and Unicode

Total characters151996
Distinct characters551
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

Unique6688 ?
Unique (%)94.8%

Sample

1st row경기도 가평군 가평읍 문화로 298
2nd row경기도 가평군 설악면 한서로 8
3rd row경기도 가평군 설악면 한서로 365
4th row경기도 가평군 설악면 유명로 1718
5th row경기도 가평군 설악면 미사리로645번길 205
ValueCountFrequency (%)
경기도 7052
 
20.7%
화성시 700
 
2.1%
남양주시 529
 
1.6%
안성시 510
 
1.5%
수원시 482
 
1.4%
평택시 457
 
1.3%
이천시 393
 
1.2%
부천시 361
 
1.1%
파주시 325
 
1.0%
여주시 309
 
0.9%
Other values (7986) 22886
67.3%
2024-03-16T04:30:39.133695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27835
 
18.3%
7381
 
4.9%
7348
 
4.8%
7162
 
4.7%
6912
 
4.5%
1 5606
 
3.7%
5284
 
3.5%
4421
 
2.9%
2 3766
 
2.5%
3 3007
 
2.0%
Other values (541) 73274
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93658
61.6%
Space Separator 27835
 
18.3%
Decimal Number 25975
 
17.1%
Dash Punctuation 1699
 
1.1%
Open Punctuation 1096
 
0.7%
Close Punctuation 1096
 
0.7%
Other Punctuation 626
 
0.4%
Uppercase Letter 9
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7381
 
7.9%
7348
 
7.8%
7162
 
7.6%
6912
 
7.4%
5284
 
5.6%
4421
 
4.7%
2416
 
2.6%
2032
 
2.2%
1907
 
2.0%
1894
 
2.0%
Other values (519) 46901
50.1%
Decimal Number
ValueCountFrequency (%)
1 5606
21.6%
2 3766
14.5%
3 3007
11.6%
4 2346
9.0%
5 2277
8.8%
6 2068
 
8.0%
7 1868
 
7.2%
0 1760
 
6.8%
8 1639
 
6.3%
9 1638
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
33.3%
B 2
22.2%
I 2
22.2%
S 1
 
11.1%
T 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 618
98.7%
. 8
 
1.3%
Space Separator
ValueCountFrequency (%)
27835
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1096
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1096
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93658
61.6%
Common 58327
38.4%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7381
 
7.9%
7348
 
7.8%
7162
 
7.6%
6912
 
7.4%
5284
 
5.6%
4421
 
4.7%
2416
 
2.6%
2032
 
2.2%
1907
 
2.0%
1894
 
2.0%
Other values (519) 46901
50.1%
Common
ValueCountFrequency (%)
27835
47.7%
1 5606
 
9.6%
2 3766
 
6.5%
3 3007
 
5.2%
4 2346
 
4.0%
5 2277
 
3.9%
6 2068
 
3.5%
7 1868
 
3.2%
0 1760
 
3.0%
- 1699
 
2.9%
Other values (6) 6095
 
10.4%
Latin
ValueCountFrequency (%)
C 3
27.3%
e 2
18.2%
B 2
18.2%
I 2
18.2%
S 1
 
9.1%
T 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93658
61.6%
ASCII 58338
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27835
47.7%
1 5606
 
9.6%
2 3766
 
6.5%
3 3007
 
5.2%
4 2346
 
4.0%
5 2277
 
3.9%
6 2068
 
3.5%
7 1868
 
3.2%
0 1760
 
3.0%
- 1699
 
2.9%
Other values (12) 6106
 
10.5%
Hangul
ValueCountFrequency (%)
7381
 
7.9%
7348
 
7.8%
7162
 
7.6%
6912
 
7.4%
5284
 
5.6%
4421
 
4.7%
2416
 
2.6%
2032
 
2.2%
1907
 
2.0%
1894
 
2.0%
Other values (519) 46901
50.1%
Distinct6864
Distinct (%)97.2%
Missing3
Missing (%)< 0.1%
Memory size55.3 KiB
2024-03-16T04:30:39.799353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length24.23237
Min length14

Characters and Unicode

Total characters171129
Distinct characters532
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

Unique6683 ?
Unique (%)94.6%

Sample

1st row경기도 가평군 가평읍 읍내리 759-2번지
2nd row경기도 가평군 설악면 신천리 156-1번지
3rd row경기도 가평군 설악면 위곡리 200-1번지
4th row경기도 가평군 설악면 선촌리 438-3번지
5th row경기도 가평군 설악면 송산리 1036-1번지
ValueCountFrequency (%)
경기도 7062
 
19.9%
화성시 700
 
2.0%
남양주시 529
 
1.5%
안성시 512
 
1.4%
수원시 482
 
1.4%
평택시 457
 
1.3%
이천시 394
 
1.1%
부천시 361
 
1.0%
파주시 325
 
0.9%
여주시 309
 
0.9%
Other values (8629) 24314
68.6%
2024-03-16T04:30:40.990620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28519
 
16.7%
7444
 
4.3%
7407
 
4.3%
7352
 
4.3%
7158
 
4.2%
6986
 
4.1%
6783
 
4.0%
1 5324
 
3.1%
4584
 
2.7%
- 4322
 
2.5%
Other values (522) 85250
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110335
64.5%
Space Separator 28519
 
16.7%
Decimal Number 27556
 
16.1%
Dash Punctuation 4322
 
2.5%
Uppercase Letter 151
 
0.1%
Open Punctuation 81
 
< 0.1%
Close Punctuation 81
 
< 0.1%
Other Punctuation 46
 
< 0.1%
Lowercase Letter 38
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7444
 
6.7%
7407
 
6.7%
7352
 
6.7%
7158
 
6.5%
6986
 
6.3%
6783
 
6.1%
4584
 
4.2%
3779
 
3.4%
2040
 
1.8%
1945
 
1.8%
Other values (473) 54857
49.7%
Uppercase Letter
ValueCountFrequency (%)
I 20
13.2%
L 15
 
9.9%
S 14
 
9.3%
H 13
 
8.6%
K 10
 
6.6%
E 10
 
6.6%
C 9
 
6.0%
A 7
 
4.6%
R 6
 
4.0%
N 6
 
4.0%
Other values (12) 41
27.2%
Decimal Number
ValueCountFrequency (%)
1 5324
19.3%
2 3608
13.1%
3 2952
10.7%
4 2709
9.8%
5 2526
9.2%
6 2362
8.6%
7 2245
8.1%
8 2105
 
7.6%
0 1900
 
6.9%
9 1825
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 25
65.8%
l 3
 
7.9%
m 2
 
5.3%
t 2
 
5.3%
h 1
 
2.6%
c 1
 
2.6%
a 1
 
2.6%
p 1
 
2.6%
i 1
 
2.6%
u 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 27
58.7%
, 18
39.1%
& 1
 
2.2%
Space Separator
ValueCountFrequency (%)
28519
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4322
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110335
64.5%
Common 60605
35.4%
Latin 189
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7444
 
6.7%
7407
 
6.7%
7352
 
6.7%
7158
 
6.5%
6986
 
6.3%
6783
 
6.1%
4584
 
4.2%
3779
 
3.4%
2040
 
1.8%
1945
 
1.8%
Other values (473) 54857
49.7%
Latin
ValueCountFrequency (%)
e 25
13.2%
I 20
 
10.6%
L 15
 
7.9%
S 14
 
7.4%
H 13
 
6.9%
K 10
 
5.3%
E 10
 
5.3%
C 9
 
4.8%
A 7
 
3.7%
R 6
 
3.2%
Other values (22) 60
31.7%
Common
ValueCountFrequency (%)
28519
47.1%
1 5324
 
8.8%
- 4322
 
7.1%
2 3608
 
6.0%
3 2952
 
4.9%
4 2709
 
4.5%
5 2526
 
4.2%
6 2362
 
3.9%
7 2245
 
3.7%
8 2105
 
3.5%
Other values (7) 3933
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110335
64.5%
ASCII 60794
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28519
46.9%
1 5324
 
8.8%
- 4322
 
7.1%
2 3608
 
5.9%
3 2952
 
4.9%
4 2709
 
4.5%
5 2526
 
4.2%
6 2362
 
3.9%
7 2245
 
3.7%
8 2105
 
3.5%
Other values (39) 4122
 
6.8%
Hangul
ValueCountFrequency (%)
7444
 
6.7%
7407
 
6.7%
7352
 
6.7%
7158
 
6.5%
6986
 
6.3%
6783
 
6.1%
4584
 
4.2%
3779
 
3.4%
2040
 
1.8%
1945
 
1.8%
Other values (473) 54857
49.7%
Distinct121
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
2024-03-16T04:30:41.532573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length10.026044
Min length3

Characters and Unicode

Total characters70834
Distinct characters128
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)0.3%

Sample

1st row경기도 가평군청
2nd row경기도 가평군청
3rd row경기도 가평군청
4th row경기도 가평군청
5th row경기도 가평군청
ValueCountFrequency (%)
경기도 6388
37.6%
화성시 700
 
4.1%
안전총괄과 630
 
3.7%
남양주시 529
 
3.1%
안전기획관 529
 
3.1%
안성시 512
 
3.0%
수원시 482
 
2.8%
평택시청 457
 
2.7%
이천시 394
 
2.3%
부천시청 361
 
2.1%
Other values (124) 6014
35.4%
2024-03-16T04:30:42.533440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9931
14.0%
6919
 
9.8%
6710
 
9.5%
6700
 
9.5%
6388
 
9.0%
3341
 
4.7%
2685
 
3.8%
1810
 
2.6%
1491
 
2.1%
1338
 
1.9%
Other values (118) 23521
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60791
85.8%
Space Separator 9931
 
14.0%
Decimal Number 112
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6919
 
11.4%
6710
 
11.0%
6700
 
11.0%
6388
 
10.5%
3341
 
5.5%
2685
 
4.4%
1810
 
3.0%
1491
 
2.5%
1338
 
2.2%
1331
 
2.2%
Other values (114) 22078
36.3%
Decimal Number
ValueCountFrequency (%)
2 49
43.8%
1 45
40.2%
3 18
 
16.1%
Space Separator
ValueCountFrequency (%)
9931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60791
85.8%
Common 10043
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6919
 
11.4%
6710
 
11.0%
6700
 
11.0%
6388
 
10.5%
3341
 
5.5%
2685
 
4.4%
1810
 
3.0%
1491
 
2.5%
1338
 
2.2%
1331
 
2.2%
Other values (114) 22078
36.3%
Common
ValueCountFrequency (%)
9931
98.9%
2 49
 
0.5%
1 45
 
0.4%
3 18
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60791
85.8%
ASCII 10043
 
14.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9931
98.9%
2 49
 
0.5%
1 45
 
0.4%
3 18
 
0.2%
Hangul
ValueCountFrequency (%)
6919
 
11.4%
6710
 
11.0%
6700
 
11.0%
6388
 
10.5%
3341
 
5.5%
2685
 
4.4%
1810
 
3.0%
1491
 
2.5%
1338
 
2.2%
1331
 
2.2%
Other values (114) 22078
36.3%
Distinct146
Distinct (%)2.3%
Missing656
Missing (%)9.3%
Memory size55.3 KiB
2024-03-16T04:30:43.256810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.257606
Min length12

Characters and Unicode

Total characters78559
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

Unique35 ?
Unique (%)0.5%

Sample

1st row031-580-2142
2nd row031-580-2142
3rd row031-580-2142
4th row031-580-2142
5th row031-580-2142
ValueCountFrequency (%)
031-5189-2346 700
 
10.9%
031-590-2892 529
 
8.3%
031-678-2995 512
 
8.0%
032-625-2863 361
 
5.6%
031-940-5712 325
 
5.1%
031-887-2553 309
 
4.8%
031-310-2458 274
 
4.3%
031-8082-6783 273
 
4.3%
031-481-3119 229
 
3.6%
031-538-2856 210
 
3.3%
Other values (136) 2687
41.9%
2024-03-16T04:30:44.276121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 12818
16.3%
0 10645
13.6%
3 10227
13.0%
1 9276
11.8%
2 8168
10.4%
8 6935
8.8%
5 5624
7.2%
9 4515
 
5.7%
6 4215
 
5.4%
4 3587
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65741
83.7%
Dash Punctuation 12818
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10645
16.2%
3 10227
15.6%
1 9276
14.1%
2 8168
12.4%
8 6935
10.5%
5 5624
8.6%
9 4515
6.9%
6 4215
 
6.4%
4 3587
 
5.5%
7 2549
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 12818
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78559
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 12818
16.3%
0 10645
13.6%
3 10227
13.0%
1 9276
11.8%
2 8168
10.4%
8 6935
8.8%
5 5624
7.2%
9 4515
 
5.7%
6 4215
 
5.4%
4 3587
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 12818
16.3%
0 10645
13.6%
3 10227
13.0%
1 9276
11.8%
2 8168
10.4%
8 6935
8.8%
5 5624
7.2%
9 4515
 
5.7%
6 4215
 
5.4%
4 3587
 
4.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6771
Distinct (%)95.9%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean37.414889
Minimum36.912084
Maximum38.213045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:44.704408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.912084
5-th percentile36.999236
Q137.219316
median37.379126
Q337.631913
95-th percentile37.870745
Maximum38.213045
Range1.300961
Interquartile range (IQR)0.41259705

Descriptive statistics

Standard deviation0.26920257
Coefficient of variation (CV)0.0071950652
Kurtosis-0.72149581
Mean37.414889
Median Absolute Deviation (MAD)0.19294642
Skewness0.26596763
Sum264223.95
Variance0.072470022
MonotonicityNot monotonic
2024-03-16T04:30:45.193604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.41301 25
 
0.4%
37.2104883 18
 
0.3%
37.395436 11
 
0.2%
37.306059 7
 
0.1%
37.299541 7
 
0.1%
37.361958 6
 
0.1%
37.611704 5
 
0.1%
37.332896 5
 
0.1%
37.327155 5
 
0.1%
37.4173 5
 
0.1%
Other values (6761) 6968
98.6%
ValueCountFrequency (%)
36.9120836 1
< 0.1%
36.9168902 1
< 0.1%
36.917507 1
< 0.1%
36.917883 1
< 0.1%
36.918108 1
< 0.1%
36.921346 1
< 0.1%
36.9236857 1
< 0.1%
36.9257698 1
< 0.1%
36.927788 1
< 0.1%
36.9290757 1
< 0.1%
ValueCountFrequency (%)
38.21304465 1
< 0.1%
38.1891275 1
< 0.1%
38.1865867 1
< 0.1%
38.1864168 1
< 0.1%
38.1828197 1
< 0.1%
38.1809133 1
< 0.1%
38.1784352 1
< 0.1%
38.1758844 1
< 0.1%
38.1742015 1
< 0.1%
38.1681556 1
< 0.1%

경도
Real number (ℝ)

Distinct6790
Distinct (%)96.1%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean127.09156
Minimum126.49547
Maximum127.79936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.2 KiB
2024-03-16T04:30:45.702543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.49547
5-th percentile126.75005
Q1126.87778
median127.05801
Q3127.24355
95-th percentile127.59124
Maximum127.79936
Range1.3038897
Interquartile range (IQR)0.36577422

Descriptive statistics

Standard deviation0.26278104
Coefficient of variation (CV)0.0020676514
Kurtosis-0.45239869
Mean127.09156
Median Absolute Deviation (MAD)0.18210315
Skewness0.49378252
Sum897520.59
Variance0.069053876
MonotonicityNot monotonic
2024-03-16T04:30:46.177258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.911433 25
 
0.4%
126.926676 11
 
0.2%
126.902211 7
 
0.1%
127.022941 7
 
0.1%
126.873186 6
 
0.1%
126.907795 5
 
0.1%
127.160257 5
 
0.1%
126.961545 5
 
0.1%
126.790704 5
 
0.1%
126.819106 5
 
0.1%
Other values (6780) 6981
98.8%
ValueCountFrequency (%)
126.495467 1
< 0.1%
126.51038 1
< 0.1%
126.5143849 1
< 0.1%
126.5145296 1
< 0.1%
126.5147191 1
< 0.1%
126.5147402 1
< 0.1%
126.5147998 1
< 0.1%
126.5150543 1
< 0.1%
126.5151191 1
< 0.1%
126.5151416 1
< 0.1%
ValueCountFrequency (%)
127.7993567472 1
< 0.1%
127.7910921485 1
< 0.1%
127.7866215204 1
< 0.1%
127.7858328 1
< 0.1%
127.7806049483 1
< 0.1%
127.7766029235 1
< 0.1%
127.7764818299 1
< 0.1%
127.772098037 1
< 0.1%
127.7711531862 1
< 0.1%
127.7704200793 1
< 0.1%
Distinct29
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size55.3 KiB
Minimum2017-06-09 00:00:00
Maximum2024-03-13 00:00:00
2024-03-16T04:30:46.667809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:47.061581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

Interactions

2024-03-16T04:30:20.317500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:10.346679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:12.295953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:14.259048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:16.078708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:18.222176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:20.650500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:10.636615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:12.745218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:14.568757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:16.392650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:18.658280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:20.910235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:11.131759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:13.012604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:14.855204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:16.759114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:18.979613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:21.306767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:11.421792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:13.289647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:15.161779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:17.048515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:19.300073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:21.603470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:11.722825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:13.573109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:15.492106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:17.453530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:19.609125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:21.914672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:12.020922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:13.955806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:15.783637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:17.829365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:30:20.024693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T04:30:47.569947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형운영시작일자운영종료일자시설면적이용가능인원수선풍기보유현황에어컨보유현황야간개방휴일개방숙박가능여부특이사항위도경도데이터기준일자
시설유형1.0000.5750.4270.4010.3830.2550.3190.1300.1370.0000.5030.3890.3640.833
운영시작일자0.5751.0000.9900.2270.0000.1620.2300.6930.8600.8770.9430.8830.8470.985
운영종료일자0.4270.9901.0000.0210.0000.1720.0980.6650.7620.0770.9670.8260.7550.987
시설면적0.4010.2270.0211.0000.8200.2940.4290.0380.0220.0000.2100.0390.0000.188
이용가능인원수0.3830.0000.0000.8201.0000.4030.5300.0770.0000.0000.3870.0430.0310.224
선풍기보유현황0.2550.1620.1720.2940.4031.0000.7150.0270.0610.0000.1730.0970.0890.239
에어컨보유현황0.3190.2300.0980.4290.5300.7151.0000.0000.0350.0000.0000.0340.0000.177
야간개방0.1300.6930.6650.0380.0770.0270.0001.0000.4290.0000.4360.3540.3680.854
휴일개방0.1370.8600.7620.0220.0000.0610.0350.4291.0000.0110.5050.5690.5430.915
숙박가능여부0.0000.8770.0770.0000.0000.0000.0000.0000.0111.000NaN0.0680.0490.191
특이사항0.5030.9430.9670.2100.3870.1730.0000.4360.505NaN1.0000.8540.5550.986
위도0.3890.8830.8260.0390.0430.0970.0340.3540.5690.0680.8541.0000.5880.935
경도0.3640.8470.7550.0000.0310.0890.0000.3680.5430.0490.5550.5881.0000.901
데이터기준일자0.8330.9850.9870.1880.2240.2390.1770.8540.9150.1910.9860.9350.9011.000
2024-03-16T04:30:48.037545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
야간개방특이사항숙박가능여부시설유형휴일개방
야간개방1.0000.3970.0000.1300.282
특이사항0.3971.0001.0000.2420.462
숙박가능여부0.0001.0001.0000.0000.007
시설유형0.1300.2420.0001.0000.137
휴일개방0.2820.4620.0070.1371.000
2024-03-16T04:30:48.360694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설면적이용가능인원수선풍기보유현황에어컨보유현황위도경도시설유형야간개방휴일개방숙박가능여부특이사항
시설면적1.0000.6610.1070.2020.0660.0910.2040.0280.0170.0000.090
이용가능인원수0.6611.0000.1250.1670.037-0.0340.1850.0770.0000.0000.229
선풍기보유현황0.1070.1251.0000.1740.042-0.0450.1360.0330.0610.0000.074
에어컨보유현황0.2020.1670.1741.0000.069-0.0640.1510.0000.0260.0000.000
위도0.0660.0370.0420.0691.000-0.0780.1280.2720.4390.0520.566
경도0.091-0.034-0.045-0.064-0.0781.0000.1190.2820.4190.0370.276
시설유형0.2040.1850.1360.1510.1280.1191.0000.1300.1370.0000.242
야간개방0.0280.0770.0330.0000.2720.2820.1301.0000.2820.0000.397
휴일개방0.0170.0000.0610.0260.4390.4190.1370.2821.0000.0070.462
숙박가능여부0.0000.0000.0000.0000.0520.0370.0000.0000.0071.0001.000
특이사항0.0900.2290.0740.0000.5660.2760.2420.3970.4621.0001.000

Missing values

2024-03-16T04:30:22.471759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T04:30:23.396696image/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.
2024-03-16T04:30:24.052287image/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

쉼터명법정동명시설유형운영시작일자운영종료일자시설면적이용가능인원수선풍기보유현황에어컨보유현황야간개방휴일개방숙박가능여부특이사항소재지도로명주소소재지지번주소관리기관명관리기관전화번호위도경도데이터기준일자
0읍내10리 경로당경기도 가평군 가평읍노인시설2023-05-202023-09-30197.03122NYN<NA>경기도 가평군 가평읍 문화로 298경기도 가평군 가평읍 읍내리 759-2번지경기도 가평군청031-580-214237.839051127.5059462023-06-07
1설악면행정복지센터경기도 가평군 설악면읍면동사무소2023-05-202023-09-30792.010005NNN<NA>경기도 가평군 설악면 한서로 8경기도 가평군 설악면 신천리 156-1번지경기도 가평군청031-580-214237.676243127.4946852023-06-07
2위곡1리 경로당경기도 가평군 설악면노인시설2023-05-202023-09-30162.04542NYN<NA>경기도 가평군 설악면 한서로 365경기도 가평군 설악면 위곡리 200-1번지경기도 가평군청031-580-214237.671597127.5290932023-06-07
3선촌2리(탐선) 경로당경기도 가평군 설악면노인시설2023-05-202023-09-30115.03321NYN<NA>경기도 가평군 설악면 유명로 1718경기도 가평군 설악면 선촌리 438-3번지경기도 가평군청031-580-214237.677028127.4799222023-06-07
4송산2리 경로당경기도 가평군 설악면노인시설2023-05-202023-09-30168.02621NYN<NA>경기도 가평군 설악면 미사리로645번길 205경기도 가평군 설악면 송산리 1036-1번지경기도 가평군청031-580-214237.720789127.5259222023-06-07
5설곡리 경로당경기도 가평군 설악면노인시설2023-05-202023-09-30165.02611NYN<NA>경기도 가평군 설악면 봉미산안길7번길 1-8경기도 가평군 설악면 설곡리 703-1번지경기도 가평군청031-580-214237.621506127.5190232023-06-07
6방일1리 경로당경기도 가평군 설악면노인시설2023-05-202023-09-30103.01602NYN<NA>경기도 가평군 설악면 양방가루재길 101경기도 가평군 설악면 방일리 104-3번지경기도 가평군청031-580-214237.629558127.500352023-06-07
7휴먼시아 경로당경기도 가평군 가평읍노인시설2023-05-202023-09-30152.06533NYN<NA>경기도 가평군 가평읍 가화로 164경기도 가평군 가평읍 읍내리 234번지 휴먼시아경기도 가평군청031-580-214237.834165127.5129092023-06-07
8상색리(벌태봉) 경로당경기도 가평군 가평읍노인시설2023-05-202023-09-30163.04512NYN<NA>경기도 가평군 가평읍 태봉두밀로 38-1경기도 가평군 가평읍 상색리 191번지경기도 가평군청031-580-214237.804359127.4825912023-06-07
9하색2리 칠악골 경로당경기도 가평군 가평읍노인시설2023-05-202023-09-30100.02102NYN<NA>경기도 가평군 가평읍 달전천벚꽃길 257-21경기도 가평군 가평읍 하색리 151-2번지경기도 가평군청031-580-214237.802623127.4947712023-06-07
쉼터명법정동명시설유형운영시작일자운영종료일자시설면적이용가능인원수선풍기보유현황에어컨보유현황야간개방휴일개방숙박가능여부특이사항소재지도로명주소소재지지번주소관리기관명관리기관전화번호위도경도데이터기준일자
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