Overview

Dataset statistics

Number of variables13
Number of observations308
Missing cells11
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.3 KiB
Average record size in memory107.4 B

Variable types

Numeric3
Categorical6
Text4

Alerts

sido has constant value ""Constant
confirm_date has constant value ""Constant
last_load_dttm has constant value ""Constant
skey is highly overall correlated with sigungu and 1 other fieldsHigh correlation
lng is highly overall correlated with sigunguHigh correlation
lat is highly overall correlated with sigunguHigh correlation
sigungu is highly overall correlated with skey and 3 other fieldsHigh correlation
target is highly overall correlated with skey and 1 other fieldsHigh correlation
target is highly imbalanced (55.9%)Imbalance
father is highly imbalanced (60.5%)Imbalance
tel has 10 (3.2%) missing valuesMissing
skey has unique valuesUnique
sj has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:30:27.248587
Analysis finished2024-04-16 11:30:28.837960
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1314.5
Minimum1161
Maximum1468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-04-16T20:30:28.894834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1161
5-th percentile1176.35
Q11237.75
median1314.5
Q31391.25
95-th percentile1452.65
Maximum1468
Range307
Interquartile range (IQR)153.5

Descriptive statistics

Standard deviation89.056162
Coefficient of variation (CV)0.067749077
Kurtosis-1.2
Mean1314.5
Median Absolute Deviation (MAD)77
Skewness0
Sum404866
Variance7931
MonotonicityNot monotonic
2024-04-16T20:30:29.011820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1385 1
 
0.3%
1254 1
 
0.3%
1261 1
 
0.3%
1260 1
 
0.3%
1259 1
 
0.3%
1258 1
 
0.3%
1257 1
 
0.3%
1256 1
 
0.3%
1255 1
 
0.3%
1253 1
 
0.3%
Other values (298) 298
96.8%
ValueCountFrequency (%)
1161 1
0.3%
1162 1
0.3%
1163 1
0.3%
1164 1
0.3%
1165 1
0.3%
1166 1
0.3%
1167 1
0.3%
1168 1
0.3%
1169 1
0.3%
1170 1
0.3%
ValueCountFrequency (%)
1468 1
0.3%
1467 1
0.3%
1466 1
0.3%
1465 1
0.3%
1464 1
0.3%
1463 1
0.3%
1462 1
0.3%
1461 1
0.3%
1460 1
0.3%
1459 1
0.3%

sido
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
부산
308 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산 308
100.0%

Length

2024-04-16T20:30:29.127459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:30:29.222439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산 308
100.0%

sigungu
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
해운대구
33 
기장군
32 
북구
30 
부산진구
26 
동래구
24 
Other values (11)
163 

Length

Max length4
Median length3
Mean length2.9318182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해운대구 33
10.7%
기장군 32
10.4%
북구 30
9.7%
부산진구 26
 
8.4%
동래구 24
 
7.8%
사상구 23
 
7.5%
사하구 22
 
7.1%
금정구 17
 
5.5%
연제구 16
 
5.2%
수영구 16
 
5.2%
Other values (6) 69
22.4%

Length

2024-04-16T20:30:29.317918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해운대구 33
10.7%
기장군 32
10.4%
북구 30
9.7%
부산진구 26
 
8.4%
동래구 24
 
7.8%
사상구 23
 
7.5%
사하구 22
 
7.1%
금정구 17
 
5.5%
연제구 16
 
5.2%
수영구 16
 
5.2%
Other values (6) 69
22.4%

sj
Text

UNIQUE 

Distinct308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-16T20:30:29.525513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.5551948
Min length3

Characters and Unicode

Total characters2635
Distinct characters241
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

Unique308 ?
Unique (%)100.0%

Sample

1st row영도구보건소
2nd row영도구청
3rd row영도도서관
4th row영도어린이영어도서관
5th row태종대유원지사업소
ValueCountFrequency (%)
동래구육아종합지원센터 2
 
0.6%
건강가정지원센터 2
 
0.6%
이케아 2
 
0.6%
영도구보건소 1
 
0.3%
반송보건지소 1
 
0.3%
이마트해운대점 1
 
0.3%
신세계백화점센텀시티점 1
 
0.3%
시립미술관 1
 
0.3%
부산반여초등학교 1
 
0.3%
부산교통공사해운대역 1
 
0.3%
Other values (301) 301
95.9%
2024-04-16T20:30:29.859915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 176
 
6.7%
산 176
 
6.7%
사 128
 
4.9%
공 114
 
4.3%
역 113
 
4.3%
교 106
 
4.0%
통 98
 
3.7%
구 56
 
2.1%
점 54
 
2.0%
동 53
 
2.0%
Other values (231) 1561
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2589
98.3%
Decimal Number 25
 
0.9%
Uppercase Letter 12
 
0.5%
Space Separator 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 176
 
6.8%
산 176
 
6.8%
사 128
 
4.9%
공 114
 
4.4%
역 113
 
4.4%
교 106
 
4.1%
통 98
 
3.8%
구 56
 
2.2%
점 54
 
2.1%
동 53
 
2.0%
Other values (221) 1515
58.5%
Decimal Number
ValueCountFrequency (%)
2 9
36.0%
1 8
32.0%
3 4
16.0%
4 2
 
8.0%
8 1
 
4.0%
0 1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
F 8
66.7%
N 2
 
16.7%
C 2
 
16.7%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2589
98.3%
Common 34
 
1.3%
Latin 12
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 176
 
6.8%
산 176
 
6.8%
사 128
 
4.9%
공 114
 
4.4%
역 113
 
4.4%
교 106
 
4.1%
통 98
 
3.8%
구 56
 
2.2%
점 54
 
2.1%
동 53
 
2.0%
Other values (221) 1515
58.5%
Common
ValueCountFrequency (%)
9
26.5%
2 9
26.5%
1 8
23.5%
3 4
11.8%
4 2
 
5.9%
8 1
 
2.9%
0 1
 
2.9%
Latin
ValueCountFrequency (%)
F 8
66.7%
N 2
 
16.7%
C 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2589
98.3%
ASCII 46
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 176
 
6.8%
산 176
 
6.8%
사 128
 
4.9%
공 114
 
4.4%
역 113
 
4.4%
교 106
 
4.1%
통 98
 
3.8%
구 56
 
2.2%
점 54
 
2.1%
동 53
 
2.0%
Other values (221) 1515
58.5%
ASCII
ValueCountFrequency (%)
9
19.6%
2 9
19.6%
F 8
17.4%
1 8
17.4%
3 4
8.7%
4 2
 
4.3%
N 2
 
4.3%
C 2
 
4.3%
8 1
 
2.2%
0 1
 
2.2%

adress
Text

Distinct292
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-16T20:30:30.152785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length20.863636
Min length11

Characters and Unicode

Total characters6426
Distinct characters222
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique279 ?
Unique (%)90.6%

Sample

1st row부산 영도구 태종로 423
2nd row부산 영도구 태종로 423
3rd row부산 영도구 함지로79번길 6
4th row부산 영도구 절영로 71
5th row부산 영도구 전망로 24
ValueCountFrequency (%)
부산 301
 
19.2%
지하 70
 
4.5%
중앙대로 34
 
2.2%
해운대구 33
 
2.1%
기장군 32
 
2.0%
북구 29
 
1.9%
부산진구 26
 
1.7%
동래구 24
 
1.5%
사상구 23
 
1.5%
사하구 22
 
1.4%
Other values (541) 970
62.0%
2024-04-16T20:30:30.520937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1256
19.5%
산 368
 
5.7%
부 363
 
5.6%
로 306
 
4.8%
구 299
 
4.7%
1 205
 
3.2%
대 186
 
2.9%
동 185
 
2.9%
2 137
 
2.1%
) 109
 
1.7%
Other values (212) 3012
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3858
60.0%
Space Separator 1256
 
19.5%
Decimal Number 981
 
15.3%
Close Punctuation 109
 
1.7%
Open Punctuation 109
 
1.7%
Other Punctuation 91
 
1.4%
Dash Punctuation 13
 
0.2%
Uppercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 368
 
9.5%
부 363
 
9.4%
로 306
 
7.9%
구 299
 
7.8%
대 186
 
4.8%
동 185
 
4.8%
하 107
 
2.8%
지 87
 
2.3%
장 80
 
2.1%
역 75
 
1.9%
Other values (192) 1802
46.7%
Decimal Number
ValueCountFrequency (%)
1 205
20.9%
2 137
14.0%
3 93
9.5%
4 89
9.1%
7 87
8.9%
0 83
8.5%
6 82
 
8.4%
5 79
 
8.1%
9 66
 
6.7%
8 60
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
E 3
33.3%
C 2
22.2%
A 2
22.2%
P 2
22.2%
Other Punctuation
ValueCountFrequency (%)
, 90
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
1256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3858
60.0%
Common 2559
39.8%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 368
 
9.5%
부 363
 
9.4%
로 306
 
7.9%
구 299
 
7.8%
대 186
 
4.8%
동 185
 
4.8%
하 107
 
2.8%
지 87
 
2.3%
장 80
 
2.1%
역 75
 
1.9%
Other values (192) 1802
46.7%
Common
ValueCountFrequency (%)
1256
49.1%
1 205
 
8.0%
2 137
 
5.4%
) 109
 
4.3%
( 109
 
4.3%
3 93
 
3.6%
, 90
 
3.5%
4 89
 
3.5%
7 87
 
3.4%
0 83
 
3.2%
Other values (6) 301
 
11.8%
Latin
ValueCountFrequency (%)
E 3
33.3%
C 2
22.2%
A 2
22.2%
P 2
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3858
60.0%
ASCII 2568
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1256
48.9%
1 205
 
8.0%
2 137
 
5.3%
) 109
 
4.2%
( 109
 
4.2%
3 93
 
3.6%
, 90
 
3.5%
4 89
 
3.5%
7 87
 
3.4%
0 83
 
3.2%
Other values (10) 310
 
12.1%
Hangul
ValueCountFrequency (%)
산 368
 
9.5%
부 363
 
9.4%
로 306
 
7.9%
구 299
 
7.8%
대 186
 
4.8%
동 185
 
4.8%
하 107
 
2.8%
지 87
 
2.3%
장 80
 
2.1%
역 75
 
1.9%
Other values (192) 1802
46.7%

place
Text

Distinct195
Distinct (%)63.5%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-04-16T20:30:30.795245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length21
Mean length8.5276873
Min length2

Characters and Unicode

Total characters2618
Distinct characters240
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)57.0%

Sample

1st row구관 출입구 근처
2nd row구청 1층
3rd row1층 어린이자료실 내
4th row3층 키즈월드 내
5th row입구 관광안내소 내
ValueCountFrequency (%)
내 116
 
15.1%
1층 98
 
12.8%
고객센터 86
 
11.2%
옆 51
 
6.6%
2층 43
 
5.6%
3층 22
 
2.9%
유아휴게실 11
 
1.4%
대합실 11
 
1.4%
안쪽 11
 
1.4%
앞 10
 
1.3%
Other values (214) 308
40.2%
2024-04-16T20:30:31.200017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
463
17.7%
층 201
 
7.7%
내 136
 
5.2%
실 126
 
4.8%
1 114
 
4.4%
터 108
 
4.1%
센 102
 
3.9%
고 92
 
3.5%
객 92
 
3.5%
옆 67
 
2.6%
Other values (230) 1117
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1916
73.2%
Space Separator 463
 
17.7%
Decimal Number 223
 
8.5%
Other Punctuation 10
 
0.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 201
 
10.5%
내 136
 
7.1%
실 126
 
6.6%
터 108
 
5.6%
센 102
 
5.3%
고 92
 
4.8%
객 92
 
4.8%
옆 67
 
3.5%
자 32
 
1.7%
원 30
 
1.6%
Other values (213) 930
48.5%
Decimal Number
ValueCountFrequency (%)
1 114
51.1%
2 55
24.7%
3 27
 
12.1%
4 11
 
4.9%
6 6
 
2.7%
5 3
 
1.3%
0 3
 
1.3%
7 2
 
0.9%
8 1
 
0.4%
9 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
. 1
 
10.0%
Space Separator
ValueCountFrequency (%)
463
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1913
73.1%
Common 701
 
26.8%
Han 3
 
0.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 201
 
10.5%
내 136
 
7.1%
실 126
 
6.6%
터 108
 
5.6%
센 102
 
5.3%
고 92
 
4.8%
객 92
 
4.8%
옆 67
 
3.5%
자 32
 
1.7%
원 30
 
1.6%
Other values (212) 927
48.5%
Common
ValueCountFrequency (%)
463
66.0%
1 114
 
16.3%
2 55
 
7.8%
3 27
 
3.9%
4 11
 
1.6%
, 9
 
1.3%
6 6
 
0.9%
5 3
 
0.4%
0 3
 
0.4%
( 2
 
0.3%
Other values (6) 8
 
1.1%
Han
ValueCountFrequency (%)
內 3
100.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1913
73.1%
ASCII 702
 
26.8%
CJK 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
463
66.0%
1 114
 
16.2%
2 55
 
7.8%
3 27
 
3.8%
4 11
 
1.6%
, 9
 
1.3%
6 6
 
0.9%
5 3
 
0.4%
0 3
 
0.4%
( 2
 
0.3%
Other values (7) 9
 
1.3%
Hangul
ValueCountFrequency (%)
층 201
 
10.5%
내 136
 
7.1%
실 126
 
6.6%
터 108
 
5.6%
센 102
 
5.3%
고 92
 
4.8%
객 92
 
4.8%
옆 67
 
3.5%
자 32
 
1.7%
원 30
 
1.6%
Other values (212) 927
48.5%
CJK
ValueCountFrequency (%)
內 3
100.0%

tel
Text

MISSING 

Distinct290
Distinct (%)97.3%
Missing10
Missing (%)3.2%
Memory size2.5 KiB
2024-04-16T20:30:31.436997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010067
Min length12

Characters and Unicode

Total characters3579
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

Unique285 ?
Unique (%)95.6%

Sample

1st row051-419-4889
2nd row051-419-4262
3rd row051-419-4835
4th row051-419-5673
5th row051-860-7867
ValueCountFrequency (%)
051-901-1715 4
 
1.3%
051-750-2388 3
 
1.0%
051-309-1772 2
 
0.7%
051-608-6022 2
 
0.7%
051-590-9042 2
 
0.7%
051-440-2281 1
 
0.3%
051-440-2264 1
 
0.3%
051-440-2266 1
 
0.3%
051-749-7634 1
 
0.3%
051-749-6536 1
 
0.3%
Other values (280) 280
94.0%
2024-04-16T20:30:31.773379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 596
16.7%
0 561
15.7%
1 544
15.2%
5 435
12.2%
6 340
9.5%
7 240
6.7%
2 220
 
6.1%
8 196
 
5.5%
4 165
 
4.6%
3 152
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2983
83.3%
Dash Punctuation 596
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 561
18.8%
1 544
18.2%
5 435
14.6%
6 340
11.4%
7 240
8.0%
2 220
 
7.4%
8 196
 
6.6%
4 165
 
5.5%
3 152
 
5.1%
9 130
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 596
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3579
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 596
16.7%
0 561
15.7%
1 544
15.2%
5 435
12.2%
6 340
9.5%
7 240
6.7%
2 220
 
6.1%
8 196
 
5.5%
4 165
 
4.6%
3 152
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 596
16.7%
0 561
15.7%
1 544
15.2%
5 435
12.2%
6 340
9.5%
7 240
6.7%
2 220
 
6.1%
8 196
 
5.5%
4 165
 
4.6%
3 152
 
4.2%

target
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
외부인
240 
외부인+직원
32 
직원+외부인
 
24
외부/직원용
 
7
직원용
 
4

Length

Max length6
Median length3
Mean length3.6103896
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
외부인 240
77.9%
외부인+직원 32
 
10.4%
직원+외부인 24
 
7.8%
외부/직원용 7
 
2.3%
직원용 4
 
1.3%
지원 1
 
0.3%

Length

2024-04-16T20:30:31.918973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:30:32.037030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외부인 240
77.9%
외부인+직원 32
 
10.4%
직원+외부인 24
 
7.8%
외부/직원용 7
 
2.3%
직원용 4
 
1.3%
지원 1
 
0.3%

father
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
가능
284 
불가
 
24

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가능 284
92.2%
불가 24
 
7.8%

Length

2024-04-16T20:30:32.132991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:30:32.209071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가능 284
92.2%
불가 24
 
7.8%

lng
Real number (ℝ)

HIGH CORRELATION 

Distinct280
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06973
Minimum128.90855
Maximum129.2484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-04-16T20:30:32.326362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.90855
5-th percentile128.96646
Q1129.01514
median129.0668
Q3129.11106
95-th percentile129.2127
Maximum129.2484
Range0.3398526
Interquartile range (IQR)0.09591265

Descriptive statistics

Standard deviation0.071589716
Coefficient of variation (CV)0.00055465921
Kurtosis-0.32671108
Mean129.06973
Median Absolute Deviation (MAD)0.04832655
Skewness0.38956294
Sum39753.478
Variance0.0051250875
MonotonicityNot monotonic
2024-04-16T20:30:32.719189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.2127825 4
 
1.3%
129.0367048 3
 
1.0%
129.2127032 3
 
1.0%
129.0679144 2
 
0.6%
129.0954831 2
 
0.6%
129.2102724 2
 
0.6%
128.9573882 2
 
0.6%
128.9914512 2
 
0.6%
129.0323514 2
 
0.6%
129.1802926 2
 
0.6%
Other values (270) 284
92.2%
ValueCountFrequency (%)
128.9085451 1
0.3%
128.9098271 1
0.3%
128.9181486 1
0.3%
128.94285 1
0.3%
128.9457317 1
0.3%
128.9499585 1
0.3%
128.9573882 2
0.6%
128.9605919 2
0.6%
128.9610531 1
0.3%
128.9623063 1
0.3%
ValueCountFrequency (%)
129.2483977 1
0.3%
129.2464003 1
0.3%
129.2349491 1
0.3%
129.2331153 1
0.3%
129.2229513 2
0.6%
129.2222856 1
0.3%
129.2218562 1
0.3%
129.2188031 1
0.3%
129.2173088 1
0.3%
129.2166515 1
0.3%

lat
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.175609
Minimum35.048443
Maximum35.382872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-04-16T20:30:32.834054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.048443
5-th percentile35.089011
Q135.138006
median35.172843
Q335.211263
95-th percentile35.271056
Maximum35.382872
Range0.33442948
Interquartile range (IQR)0.07325693

Descriptive statistics

Standard deviation0.058448238
Coefficient of variation (CV)0.0016616127
Kurtosis0.62626728
Mean35.175609
Median Absolute Deviation (MAD)0.03596366
Skewness0.47673434
Sum10834.088
Variance0.0034161966
MonotonicityNot monotonic
2024-04-16T20:30:32.967350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1922105 4
 
1.3%
35.20459614 3
 
1.0%
35.09830894 3
 
1.0%
35.1944042 2
 
0.6%
35.3255014 2
 
0.6%
35.18002552 2
 
0.6%
35.19028869 2
 
0.6%
35.16545076 2
 
0.6%
35.15254688 2
 
0.6%
35.16433176 2
 
0.6%
Other values (269) 284
92.2%
ValueCountFrequency (%)
35.04844266 1
0.3%
35.05041 1
0.3%
35.05711963 1
0.3%
35.05969475 1
0.3%
35.06522442 1
0.3%
35.07394528 1
0.3%
35.07526852 1
0.3%
35.075886 1
0.3%
35.07675264 1
0.3%
35.07856617 2
0.6%
ValueCountFrequency (%)
35.38287214 1
0.3%
35.37752079 1
0.3%
35.33280963 1
0.3%
35.32679501 1
0.3%
35.32632973 1
0.3%
35.3255014 2
0.6%
35.32528904 1
0.3%
35.32372898 1
0.3%
35.32305178 1
0.3%
35.28912199 2
0.6%

confirm_date
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2020-12-31
308 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-31
2nd row2020-12-31
3rd row2020-12-31
4th row2020-12-31
5th row2020-12-31

Common Values

ValueCountFrequency (%)
2020-12-31 308
100.0%

Length

2024-04-16T20:30:33.081207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:30:33.162623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-31 308
100.0%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2021-04-01 06:02:03
308 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-01 06:02:03
2nd row2021-04-01 06:02:03
3rd row2021-04-01 06:02:03
4th row2021-04-01 06:02:03
5th row2021-04-01 06:02:03

Common Values

ValueCountFrequency (%)
2021-04-01 06:02:03 308
100.0%

Length

2024-04-16T20:30:33.250342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:30:33.331121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-01 308
50.0%
06:02:03 308
50.0%

Interactions

2024-04-16T20:30:28.294819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:27.789414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:28.055508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:28.365889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:27.869501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:28.138818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:28.444778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:27.966044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:30:28.214609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-16T20:30:33.393308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeysigungutargetfatherlnglat
skey1.0000.9780.8060.0750.9040.798
sigungu0.9781.0000.8610.1110.8980.858
target0.8060.8611.0000.3420.6620.540
father0.0750.1110.3421.0000.0000.081
lng0.9040.8980.6620.0001.0000.754
lat0.7980.8580.5400.0810.7541.000
2024-04-16T20:30:33.494544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
targetfathersigungu
target1.0000.2450.630
father0.2451.0000.084
sigungu0.6300.0841.000
2024-04-16T20:30:33.587204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeylnglatsigungutargetfather
skey1.0000.2520.3300.8880.5930.055
lng0.2521.0000.4080.6420.4320.074
lat0.3300.4081.0000.5560.3190.060
sigungu0.8880.6420.5561.0000.6300.084
target0.5930.4320.3190.6301.0000.245
father0.0550.0740.0600.0840.2451.000

Missing values

2024-04-16T20:30:28.546928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T20:30:28.692482image/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.
2024-04-16T20:30:28.795833image/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

skeysidosigungusjadressplaceteltargetfatherlnglatconfirm_datelast_load_dttm
01385부산영도구영도구보건소부산 영도구 태종로 423구관 출입구 근처051-419-4889외부인가능129.06791435.0912142020-12-312021-04-01 06:02:03
11386부산영도구영도구청부산 영도구 태종로 423구청 1층051-419-4262외부인가능129.06791435.0912142020-12-312021-04-01 06:02:03
21387부산영도구영도도서관부산 영도구 함지로79번길 61층 어린이자료실 내051-419-4835외부인가능129.06686235.0752692020-12-312021-04-01 06:02:03
31388부산영도구영도어린이영어도서관부산 영도구 절영로 713층 키즈월드 내051-419-5673외부인가능129.03892935.0886092020-12-312021-04-01 06:02:03
41389부산영도구태종대유원지사업소부산 영도구 전망로 24입구 관광안내소 내051-860-7867외부인가능129.07980335.0596952020-12-312021-04-01 06:02:03
51390부산영도구영도문화예술회관부산광역시 영도구 함지로79번길 6지하1층051-419-5561외부인가능129.06655435.0758862020-12-312021-04-01 06:02:03
61391부산연제구거제종합사회복지관부산 연제구 아시아드대로46번길 452층 아동신나는 놀이터안051-507-8173외부인가능129.07070235.1884772020-12-312021-04-01 06:02:03
71392부산연제구부산고등법원부산 연제구 법원로 311층 종합민원실 맞은편051-590-1110외부인가능129.0732735.1925372020-12-312021-04-01 06:02:03
81393부산연제구부산교통공사교대역부산 연제구 중앙대로 지하 1217 (거제동, 도시철도 교대역)고객센터 내051-678-6124외부인가능129.07927935.1960082020-12-312021-04-01 06:02:03
91394부산연제구부산교통공사시청역부산 연제구 중앙대로 지하 1017 (연산동, 도시철도 시청역)고객센터 내051-678-6122외부인가능129.07662735.179782020-12-312021-04-01 06:02:03
skeysidosigungusjadressplaceteltargetfatherlnglatconfirm_datelast_load_dttm
2981459부산북구부산북구육아종합지원센터부산 북구 만덕1로104번가길 37 (만덕동)1층051-342-6161외부인불가129.0284435.2162822020-12-312021-04-01 06:02:03
2991460부산북구부산시인재개발원부산 북구 효열로 2563층 모성상담실 맞은편051-366-7583외부인가능129.02113935.2681742020-12-312021-04-01 06:02:03
3001461부산북구북구청부산 북구 낙동대로1570번길 331층 노조사무실 옆051-309-4376외부인가능128.99009135.196882020-12-312021-04-01 06:02:03
3011462부산북구시립구포도서관부산 북구 백양대로1016번다길 431층 어린이도서관 안051-330-6344외부인가능128.99600735.1939742020-12-312021-04-01 06:02:03
3021463부산북구코레일구포역부산 북구 구포만세길 82 (구포동, 구포역)2층 고객대기실 내051-440-2495외부인가능128.99714735.2054752020-12-312021-04-01 06:02:03
3031464부산북구한국방송통신대학교부산부산 북구 학사로17번길 141층 유아방 내051-361-9905외부인불가129.00648135.2240292020-12-312021-04-01 06:02:03
3041465부산북구화명1동주민센터부산 북구 금곡대로 274민원실 안쪽 상담실내051-309-6312외부인가능129.01378535.2327842020-12-312021-04-01 06:02:03
3051466부산북구화명2동주민센터부산 북구 양달로 581층 상담실051-309-6324외부인가능129.01984235.2436132020-12-312021-04-01 06:02:03
3061467부산북구화명3동주민센터부산 북구 화명신도시로 851층 당직실051-309-6353외부인가능129.01004935.2318692020-12-312021-04-01 06:02:03
3071468부산북구부산 건강가정지원센터부산북구 효열로 2561층 정보자료실내051-330-3474외부인불가129.02113935.2681742020-12-312021-04-01 06:02:03