Overview

Dataset statistics

Number of variables16
Number of observations2946
Missing cells5489
Missing cells (%)11.6%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory377.0 KiB
Average record size in memory131.0 B

Variable types

Text9
Categorical2
DateTime2
Numeric2
Unsupported1

Alerts

last_load_dttm has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
qty is highly imbalanced (81.3%)Imbalance
skey has 31 (1.1%) missing valuesMissing
seq has 456 (15.5%) missing valuesMissing
addr_road has 80 (2.7%) missing valuesMissing
addr_jibun has 1372 (46.6%) missing valuesMissing
manager has 66 (2.2%) missing valuesMissing
tel has 66 (2.2%) missing valuesMissing
data_day has 66 (2.2%) missing valuesMissing
lat has 109 (3.7%) missing valuesMissing
lng has 109 (3.7%) missing valuesMissing
apr_at has 2946 (100.0%) missing valuesMissing
last_load_dttm has 108 (3.7%) missing valuesMissing
apr_at is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 16:01:56.130478
Analysis finished2024-04-17 16:01:58.138684
Duration2.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

MISSING 

Distinct2915
Distinct (%)100.0%
Missing31
Missing (%)1.1%
Memory size23.1 KiB
2024-04-18T01:01:58.370248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length5
Mean length5.0765009
Min length5

Characters and Unicode

Total characters14798
Distinct characters96
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2915 ?
Unique (%)100.0%

Sample

1st row47167
2nd row47168
3rd row47169
4th row47170
5th row47171
ValueCountFrequency (%)
앞 7
 
0.2%
맞은편 5
 
0.2%
위 4
 
0.1%
1 2
 
0.1%
수정동 2
 
0.1%
옆 2
 
0.1%
수정공원로 2
 
0.1%
망양로 2
 
0.1%
46883 1
 
< 0.1%
46726 1
 
< 0.1%
Other values (2935) 2935
99.1%
2024-04-18T01:01:58.758869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 4502
30.4%
5 1639
 
11.1%
6 1618
 
10.9%
7 1258
 
8.5%
3 990
 
6.7%
0 953
 
6.4%
1 941
 
6.4%
8 912
 
6.2%
9 848
 
5.7%
2 801
 
5.4%
Other values (86) 336
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14462
97.7%
Other Letter 210
 
1.4%
Space Separator 50
 
0.3%
Open Punctuation 35
 
0.2%
Close Punctuation 35
 
0.2%
Dash Punctuation 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 18
 
8.6%
정 10
 
4.8%
수 10
 
4.8%
길 8
 
3.8%
앞 7
 
3.3%
양 7
 
3.3%
동 6
 
2.9%
망 6
 
2.9%
번 6
 
2.9%
맞 5
 
2.4%
Other values (71) 127
60.5%
Decimal Number
ValueCountFrequency (%)
4 4502
31.1%
5 1639
 
11.3%
6 1618
 
11.2%
7 1258
 
8.7%
3 990
 
6.8%
0 953
 
6.6%
1 941
 
6.5%
8 912
 
6.3%
9 848
 
5.9%
2 801
 
5.5%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14588
98.6%
Hangul 210
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 18
 
8.6%
정 10
 
4.8%
수 10
 
4.8%
길 8
 
3.8%
앞 7
 
3.3%
양 7
 
3.3%
동 6
 
2.9%
망 6
 
2.9%
번 6
 
2.9%
맞 5
 
2.4%
Other values (71) 127
60.5%
Common
ValueCountFrequency (%)
4 4502
30.9%
5 1639
 
11.2%
6 1618
 
11.1%
7 1258
 
8.6%
3 990
 
6.8%
0 953
 
6.5%
1 941
 
6.5%
8 912
 
6.3%
9 848
 
5.8%
2 801
 
5.5%
Other values (5) 126
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14588
98.6%
Hangul 210
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 4502
30.9%
5 1639
 
11.2%
6 1618
 
11.1%
7 1258
 
8.6%
3 990
 
6.8%
0 953
 
6.5%
1 941
 
6.5%
8 912
 
6.3%
9 848
 
5.8%
2 801
 
5.5%
Other values (5) 126
 
0.9%
Hangul
ValueCountFrequency (%)
로 18
 
8.6%
정 10
 
4.8%
수 10
 
4.8%
길 8
 
3.8%
앞 7
 
3.3%
양 7
 
3.3%
동 6
 
2.9%
망 6
 
2.9%
번 6
 
2.9%
맞 5
 
2.4%
Other values (71) 127
60.5%

instt_code
Text

Distinct54
Distinct (%)1.8%
Missing27
Missing (%)0.9%
Memory size23.1 KiB
2024-04-18T01:01:58.899216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length7
Mean length7.1397739
Min length7

Characters and Unicode

Total characters20841
Distinct characters53
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

Unique37 ?
Unique (%)1.3%

Sample

1st row3340000
2nd row3340000
3rd row3340000
4th row3340000
5th row3340000
ValueCountFrequency (%)
3290000 330
10.9%
3340000 315
10.4%
3330000 304
10.0%
3390000 279
9.2%
3270000 240
 
7.9%
3350000 232
 
7.6%
3370000 193
 
6.3%
3310000 167
 
5.5%
3300000 154
 
5.1%
3320000 132
 
4.3%
Other values (76) 694
22.8%
2024-04-18T01:01:59.364636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11709
56.2%
3 5199
24.9%
2 996
 
4.8%
9 616
 
3.0%
7 444
 
2.1%
4 347
 
1.7%
5 318
 
1.5%
6 231
 
1.1%
8 217
 
1.0%
1 192
 
0.9%
Other values (43) 572
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20269
97.3%
Other Letter 446
 
2.1%
Space Separator 121
 
0.6%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 46
10.3%
동 43
9.6%
구 42
9.4%
광 39
 
8.7%
시 39
 
8.7%
역 39
 
8.7%
부 39
 
8.7%
로 38
 
8.5%
길 12
 
2.7%
번 11
 
2.5%
Other values (31) 98
22.0%
Decimal Number
ValueCountFrequency (%)
0 11709
57.8%
3 5199
25.7%
2 996
 
4.9%
9 616
 
3.0%
7 444
 
2.2%
4 347
 
1.7%
5 318
 
1.6%
6 231
 
1.1%
8 217
 
1.1%
1 192
 
0.9%
Space Separator
ValueCountFrequency (%)
121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20395
97.9%
Hangul 446
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 46
10.3%
동 43
9.6%
구 42
9.4%
광 39
 
8.7%
시 39
 
8.7%
역 39
 
8.7%
부 39
 
8.7%
로 38
 
8.5%
길 12
 
2.7%
번 11
 
2.5%
Other values (31) 98
22.0%
Common
ValueCountFrequency (%)
0 11709
57.4%
3 5199
25.5%
2 996
 
4.9%
9 616
 
3.0%
7 444
 
2.2%
4 347
 
1.7%
5 318
 
1.6%
6 231
 
1.1%
8 217
 
1.1%
1 192
 
0.9%
Other values (2) 126
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20395
97.9%
Hangul 446
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11709
57.4%
3 5199
25.5%
2 996
 
4.9%
9 616
 
3.0%
7 444
 
2.2%
4 347
 
1.7%
5 318
 
1.6%
6 231
 
1.1%
8 217
 
1.1%
1 192
 
0.9%
Other values (2) 126
 
0.6%
Hangul
ValueCountFrequency (%)
산 46
10.3%
동 43
9.6%
구 42
9.4%
광 39
 
8.7%
시 39
 
8.7%
역 39
 
8.7%
부 39
 
8.7%
로 38
 
8.5%
길 12
 
2.7%
번 11
 
2.5%
Other values (31) 98
22.0%

admns_nm
Text

Distinct232
Distinct (%)7.9%
Missing25
Missing (%)0.8%
Memory size23.1 KiB
2024-04-18T01:01:59.612987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length4
Mean length3.9753509
Min length3

Characters and Unicode

Total characters11612
Distinct characters114
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

Unique42 ?
Unique (%)1.4%

Sample

1st row다대2동
2nd row다대2동
3rd row다대2동
4th row구평동
5th row구평동
ValueCountFrequency (%)
지사동 57
 
1.9%
주례2동 57
 
1.9%
중2동 57
 
1.9%
재송2동 54
 
1.8%
개금3동 50
 
1.6%
범일1동 50
 
1.6%
엄궁동 49
 
1.6%
연산9동 46
 
1.5%
청룡노포동 42
 
1.4%
부산광역시 41
 
1.3%
Other values (228) 2543
83.5%
2024-04-18T01:01:59.978338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3007
25.9%
2 821
 
7.1%
1 746
 
6.4%
3 314
 
2.7%
정 223
 
1.9%
천 219
 
1.9%
산 211
 
1.8%
대 192
 
1.7%
연 192
 
1.7%
4 179
 
1.5%
Other values (104) 5508
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9114
78.5%
Decimal Number 2297
 
19.8%
Space Separator 163
 
1.4%
Dash Punctuation 38
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3007
33.0%
정 223
 
2.4%
천 219
 
2.4%
산 211
 
2.3%
대 192
 
2.1%
연 192
 
2.1%
장 177
 
1.9%
구 176
 
1.9%
송 162
 
1.8%
포 146
 
1.6%
Other values (92) 4409
48.4%
Decimal Number
ValueCountFrequency (%)
2 821
35.7%
1 746
32.5%
3 314
 
13.7%
4 179
 
7.8%
6 58
 
2.5%
9 55
 
2.4%
5 52
 
2.3%
8 31
 
1.3%
7 22
 
1.0%
0 19
 
0.8%
Space Separator
ValueCountFrequency (%)
163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9114
78.5%
Common 2498
 
21.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3007
33.0%
정 223
 
2.4%
천 219
 
2.4%
산 211
 
2.3%
대 192
 
2.1%
연 192
 
2.1%
장 177
 
1.9%
구 176
 
1.9%
송 162
 
1.8%
포 146
 
1.6%
Other values (92) 4409
48.4%
Common
ValueCountFrequency (%)
2 821
32.9%
1 746
29.9%
3 314
 
12.6%
4 179
 
7.2%
163
 
6.5%
6 58
 
2.3%
9 55
 
2.2%
5 52
 
2.1%
- 38
 
1.5%
8 31
 
1.2%
Other values (2) 41
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9114
78.5%
ASCII 2498
 
21.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3007
33.0%
정 223
 
2.4%
천 219
 
2.4%
산 211
 
2.3%
대 192
 
2.1%
연 192
 
2.1%
장 177
 
1.9%
구 176
 
1.9%
송 162
 
1.8%
포 146
 
1.6%
Other values (92) 4409
48.4%
ASCII
ValueCountFrequency (%)
2 821
32.9%
1 746
29.9%
3 314
 
12.6%
4 179
 
7.2%
163
 
6.5%
6 58
 
2.3%
9 55
 
2.2%
5 52
 
2.1%
- 38
 
1.5%
8 31
 
1.2%
Other values (2) 41
 
1.6%

seq
Text

MISSING 

Distinct2034
Distinct (%)81.7%
Missing456
Missing (%)15.5%
Memory size23.1 KiB
2024-04-18T01:02:00.236102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1024096
Min length1

Characters and Unicode

Total characters12705
Distinct characters70
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1880 ?
Unique (%)75.5%

Sample

1st row주례-54
2nd row주례-55
3rd row주례-56
4th row주례-57
5th row주례-13
ValueCountFrequency (%)
1 58
 
2.3%
3 16
 
0.6%
2 16
 
0.6%
4 16
 
0.6%
5 15
 
0.6%
6 13
 
0.5%
7 12
 
0.5%
10 10
 
0.4%
8 10
 
0.4%
11 10
 
0.4%
Other values (2024) 2314
92.9%
2024-04-18T01:02:00.582890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1955
15.4%
1 1531
 
12.1%
동 1018
 
8.0%
2 1005
 
7.9%
0 805
 
6.3%
3 590
 
4.6%
4 483
 
3.8%
5 397
 
3.1%
구 360
 
2.8%
6 347
 
2.7%
Other values (60) 4214
33.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6005
47.3%
Other Letter 4513
35.5%
Dash Punctuation 1955
 
15.4%
Uppercase Letter 209
 
1.6%
Lowercase Letter 23
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1018
22.6%
구 360
 
8.0%
연 204
 
4.5%
남 198
 
4.4%
제 193
 
4.3%
송 162
 
3.6%
정 133
 
2.9%
초 106
 
2.3%
반 102
 
2.3%
범 95
 
2.1%
Other values (46) 1942
43.0%
Decimal Number
ValueCountFrequency (%)
1 1531
25.5%
2 1005
16.7%
0 805
13.4%
3 590
 
9.8%
4 483
 
8.0%
5 397
 
6.6%
6 347
 
5.8%
7 299
 
5.0%
8 280
 
4.7%
9 268
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 106
50.7%
A 103
49.3%
Dash Punctuation
ValueCountFrequency (%)
- 1955
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7960
62.7%
Hangul 4513
35.5%
Latin 232
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1018
22.6%
구 360
 
8.0%
연 204
 
4.5%
남 198
 
4.4%
제 193
 
4.3%
송 162
 
3.6%
정 133
 
2.9%
초 106
 
2.3%
반 102
 
2.3%
범 95
 
2.1%
Other values (46) 1942
43.0%
Common
ValueCountFrequency (%)
- 1955
24.6%
1 1531
19.2%
2 1005
12.6%
0 805
10.1%
3 590
 
7.4%
4 483
 
6.1%
5 397
 
5.0%
6 347
 
4.4%
7 299
 
3.8%
8 280
 
3.5%
Latin
ValueCountFrequency (%)
B 106
45.7%
A 103
44.4%
a 23
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8192
64.5%
Hangul 4513
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1955
23.9%
1 1531
18.7%
2 1005
12.3%
0 805
9.8%
3 590
 
7.2%
4 483
 
5.9%
5 397
 
4.8%
6 347
 
4.2%
7 299
 
3.6%
8 280
 
3.4%
Other values (4) 500
 
6.1%
Hangul
ValueCountFrequency (%)
동 1018
22.6%
구 360
 
8.0%
연 204
 
4.5%
남 198
 
4.4%
제 193
 
4.3%
송 162
 
3.6%
정 133
 
2.9%
초 106
 
2.3%
반 102
 
2.3%
범 95
 
2.1%
Other values (46) 1942
43.0%

spot
Text

Distinct2128
Distinct (%)72.9%
Missing28
Missing (%)1.0%
Memory size23.1 KiB
2024-04-18T01:02:00.783893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length36
Mean length12.403701
Min length2

Characters and Unicode

Total characters36194
Distinct characters603
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1835 ?
Unique (%)62.9%

Sample

1st row다대종합사회복지관건너편화단
2nd row다대종합사회복지관 앞
3rd row다대로381 앞
4th row용화사 앞
5th row두송로 155 건너편
ValueCountFrequency (%)
앞 546
 
7.5%
입구 190
 
2.6%
옆 149
 
2.0%
맞은편 125
 
1.7%
부산광역시 118
 
1.6%
강서구 117
 
1.6%
도로 114
 
1.6%
주민센터 71
 
1.0%
정문 67
 
0.9%
주례2동 57
 
0.8%
Other values (3127) 5771
78.8%
2024-04-18T01:02:01.113339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4576
 
12.6%
동 1286
 
3.6%
로 1269
 
3.5%
1 891
 
2.5%
앞 786
 
2.2%
( 693
 
1.9%
) 693
 
1.9%
2 684
 
1.9%
구 627
 
1.7%
3 475
 
1.3%
Other values (593) 24214
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25810
71.3%
Space Separator 4576
 
12.6%
Decimal Number 3820
 
10.6%
Open Punctuation 693
 
1.9%
Close Punctuation 693
 
1.9%
Uppercase Letter 181
 
0.5%
Other Punctuation 180
 
0.5%
Dash Punctuation 179
 
0.5%
Math Symbol 37
 
0.1%
Lowercase Letter 22
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1286
 
5.0%
로 1269
 
4.9%
앞 786
 
3.0%
구 627
 
2.4%
대 465
 
1.8%
산 435
 
1.7%
주 433
 
1.7%
정 415
 
1.6%
길 406
 
1.6%
입 405
 
1.6%
Other values (538) 19283
74.7%
Uppercase Letter
ValueCountFrequency (%)
S 30
16.6%
C 28
15.5%
I 18
9.9%
K 15
8.3%
G 14
 
7.7%
A 11
 
6.1%
L 9
 
5.0%
R 8
 
4.4%
T 7
 
3.9%
B 6
 
3.3%
Other values (10) 35
19.3%
Decimal Number
ValueCountFrequency (%)
1 891
23.3%
2 684
17.9%
3 475
12.4%
4 321
 
8.4%
0 298
 
7.8%
5 250
 
6.5%
6 241
 
6.3%
7 224
 
5.9%
9 221
 
5.8%
8 215
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
m 5
22.7%
t 4
18.2%
e 4
18.2%
s 3
13.6%
k 2
 
9.1%
c 1
 
4.5%
i 1
 
4.5%
g 1
 
4.5%
a 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
@ 99
55.0%
, 69
38.3%
: 5
 
2.8%
. 3
 
1.7%
& 2
 
1.1%
/ 1
 
0.6%
· 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 30
81.1%
→ 4
 
10.8%
> 2
 
5.4%
～ 1
 
2.7%
Space Separator
ValueCountFrequency (%)
4576
100.0%
Open Punctuation
ValueCountFrequency (%)
( 693
100.0%
Close Punctuation
ValueCountFrequency (%)
) 693
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 179
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25812
71.3%
Common 10178
 
28.1%
Latin 203
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1286
 
5.0%
로 1269
 
4.9%
앞 786
 
3.0%
구 627
 
2.4%
대 465
 
1.8%
산 435
 
1.7%
주 433
 
1.7%
정 415
 
1.6%
길 406
 
1.6%
입 405
 
1.6%
Other values (538) 19285
74.7%
Latin
ValueCountFrequency (%)
S 30
14.8%
C 28
13.8%
I 18
 
8.9%
K 15
 
7.4%
G 14
 
6.9%
A 11
 
5.4%
L 9
 
4.4%
R 8
 
3.9%
T 7
 
3.4%
B 6
 
3.0%
Other values (19) 57
28.1%
Common
ValueCountFrequency (%)
4576
45.0%
1 891
 
8.8%
( 693
 
6.8%
) 693
 
6.8%
2 684
 
6.7%
3 475
 
4.7%
4 321
 
3.2%
0 298
 
2.9%
5 250
 
2.5%
6 241
 
2.4%
Other values (15) 1056
 
10.4%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25809
71.3%
ASCII 10375
28.7%
None 5
 
< 0.1%
Arrows 4
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4576
44.1%
1 891
 
8.6%
( 693
 
6.7%
) 693
 
6.7%
2 684
 
6.6%
3 475
 
4.6%
4 321
 
3.1%
0 298
 
2.9%
5 250
 
2.4%
6 241
 
2.3%
Other values (41) 1253
 
12.1%
Hangul
ValueCountFrequency (%)
동 1286
 
5.0%
로 1269
 
4.9%
앞 786
 
3.0%
구 627
 
2.4%
대 465
 
1.8%
산 435
 
1.7%
주 433
 
1.7%
정 415
 
1.6%
길 406
 
1.6%
입 405
 
1.6%
Other values (537) 19282
74.7%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 1
 
20.0%
～ 1
 
20.0%
CJK
ValueCountFrequency (%)
舊 1
100.0%

addr_road
Text

MISSING 

Distinct2265
Distinct (%)79.0%
Missing80
Missing (%)2.7%
Memory size23.1 KiB
2024-04-18T01:02:01.423836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length28
Mean length17.139218
Min length2

Characters and Unicode

Total characters49121
Distinct characters280
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1898 ?
Unique (%)66.2%

Sample

1st row부산광역시 사하구 다대로 381(다대동)
2nd row부산광역시 사하구 다대로 440(다대동)
3rd row부산광역시 사하구 다대로 381(다대동)
4th row부산광역시 사하구 감천항로190번길 47-7(구평동)
5th row부산광역시 사하구 두송로 155(구평동)
ValueCountFrequency (%)
부산광역시 2145
 
21.5%
사하구 312
 
3.1%
사상구 279
 
2.8%
금정구 232
 
2.3%
동구 198
 
2.0%
연제구 191
 
1.9%
남구 167
 
1.7%
동래구 147
 
1.5%
북구 133
 
1.3%
강서구 115
 
1.2%
Other values (2182) 6070
60.8%
2024-04-18T01:02:01.831007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7217
 
14.7%
산 2540
 
5.2%
로 2417
 
4.9%
구 2245
 
4.6%
광 2214
 
4.5%
시 2191
 
4.5%
부 2172
 
4.4%
역 2146
 
4.4%
1 1923
 
3.9%
2 1345
 
2.7%
Other values (270) 22711
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30409
61.9%
Decimal Number 9945
 
20.2%
Space Separator 7217
 
14.7%
Open Punctuation 523
 
1.1%
Close Punctuation 523
 
1.1%
Dash Punctuation 482
 
1.0%
Other Punctuation 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2540
 
8.4%
로 2417
 
7.9%
구 2245
 
7.4%
광 2214
 
7.3%
시 2191
 
7.2%
부 2172
 
7.1%
역 2146
 
7.1%
동 1321
 
4.3%
길 1115
 
3.7%
번 1052
 
3.5%
Other values (253) 10996
36.2%
Decimal Number
ValueCountFrequency (%)
1 1923
19.3%
2 1345
13.5%
3 1114
11.2%
4 1010
10.2%
5 884
8.9%
6 813
8.2%
7 808
8.1%
0 728
 
7.3%
9 664
 
6.7%
8 656
 
6.6%
Open Punctuation
ValueCountFrequency (%)
( 522
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 522
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
7217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 482
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30409
61.9%
Common 18712
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2540
 
8.4%
로 2417
 
7.9%
구 2245
 
7.4%
광 2214
 
7.3%
시 2191
 
7.2%
부 2172
 
7.1%
역 2146
 
7.1%
동 1321
 
4.3%
길 1115
 
3.7%
번 1052
 
3.5%
Other values (253) 10996
36.2%
Common
ValueCountFrequency (%)
7217
38.6%
1 1923
 
10.3%
2 1345
 
7.2%
3 1114
 
6.0%
4 1010
 
5.4%
5 884
 
4.7%
6 813
 
4.3%
7 808
 
4.3%
0 728
 
3.9%
9 664
 
3.5%
Other values (7) 2206
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30409
61.9%
ASCII 18712
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7217
38.6%
1 1923
 
10.3%
2 1345
 
7.2%
3 1114
 
6.0%
4 1010
 
5.4%
5 884
 
4.7%
6 813
 
4.3%
7 808
 
4.3%
0 728
 
3.9%
9 664
 
3.5%
Other values (7) 2206
 
11.8%
Hangul
ValueCountFrequency (%)
산 2540
 
8.4%
로 2417
 
7.9%
구 2245
 
7.4%
광 2214
 
7.3%
시 2191
 
7.2%
부 2172
 
7.1%
역 2146
 
7.1%
동 1321
 
4.3%
길 1115
 
3.7%
번 1052
 
3.5%
Other values (253) 10996
36.2%

addr_jibun
Text

MISSING 

Distinct1173
Distinct (%)74.5%
Missing1372
Missing (%)46.6%
Memory size23.1 KiB
2024-04-18T01:02:02.098753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length17.378018
Min length2

Characters and Unicode

Total characters27353
Distinct characters175
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique889 ?
Unique (%)56.5%

Sample

1st row부산광역시 사하구 다대동 93-3
2nd row부산광역시 사하구 다대동 113-12
3rd row부산광역시 사하구 다대동 93-3
4th row부산광역시 사하구 구평동 272
5th row부산광역시 사하구 구평동 435-102
ValueCountFrequency (%)
부산광역시 1264
22.2%
사하구 315
 
5.5%
동구 239
 
4.2%
동래구 132
 
2.3%
북구 131
 
2.3%
강서구 116
 
2.0%
수영구 110
 
1.9%
영도구 100
 
1.8%
중구 74
 
1.3%
괴정동 70
 
1.2%
Other values (1326) 3151
55.3%
2024-04-18T01:02:02.468379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4248
 
15.5%
동 1826
 
6.7%
1 1541
 
5.6%
산 1386
 
5.1%
구 1325
 
4.8%
광 1316
 
4.8%
부 1274
 
4.7%
시 1269
 
4.6%
역 1264
 
4.6%
- 1123
 
4.1%
Other values (165) 10781
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15195
55.6%
Decimal Number 6667
24.4%
Space Separator 4348
 
15.9%
Dash Punctuation 1123
 
4.1%
Math Symbol 20
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1826
12.0%
산 1386
 
9.1%
구 1325
 
8.7%
광 1316
 
8.7%
부 1274
 
8.4%
시 1269
 
8.4%
역 1264
 
8.3%
사 428
 
2.8%
하 329
 
2.2%
영 260
 
1.7%
Other values (151) 4518
29.7%
Decimal Number
ValueCountFrequency (%)
1 1541
23.1%
2 834
12.5%
3 670
10.0%
4 630
9.4%
5 597
 
9.0%
6 530
 
7.9%
0 487
 
7.3%
7 474
 
7.1%
8 471
 
7.1%
9 433
 
6.5%
Space Separator
ValueCountFrequency (%)
4248
97.7%
  100
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1123
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15195
55.6%
Common 12158
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1826
12.0%
산 1386
 
9.1%
구 1325
 
8.7%
광 1316
 
8.7%
부 1274
 
8.4%
시 1269
 
8.4%
역 1264
 
8.3%
사 428
 
2.8%
하 329
 
2.2%
영 260
 
1.7%
Other values (151) 4518
29.7%
Common
ValueCountFrequency (%)
4248
34.9%
1 1541
 
12.7%
- 1123
 
9.2%
2 834
 
6.9%
3 670
 
5.5%
4 630
 
5.2%
5 597
 
4.9%
6 530
 
4.4%
0 487
 
4.0%
7 474
 
3.9%
Other values (4) 1024
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15195
55.6%
ASCII 12058
44.1%
None 100
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4248
35.2%
1 1541
 
12.8%
- 1123
 
9.3%
2 834
 
6.9%
3 670
 
5.6%
4 630
 
5.2%
5 597
 
5.0%
6 530
 
4.4%
0 487
 
4.0%
7 474
 
3.9%
Other values (3) 924
 
7.7%
Hangul
ValueCountFrequency (%)
동 1826
12.0%
산 1386
 
9.1%
구 1325
 
8.7%
광 1316
 
8.7%
부 1274
 
8.4%
시 1269
 
8.4%
역 1264
 
8.3%
사 428
 
2.8%
하 329
 
2.2%
영 260
 
1.7%
Other values (151) 4518
29.7%
None
ValueCountFrequency (%)
  100
100.0%

qty
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
1
2583 
2
 
139
<NA>
 
66
3
 
44
2020-10-08
 
38
Other values (23)
 
76

Length

Max length10
Median length1
Mean length1.2057026
Min length1

Unique

Unique13 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2583
87.7%
2 139
 
4.7%
<NA> 66
 
2.2%
3 44
 
1.5%
2020-10-08 38
 
1.3%
4 17
 
0.6%
5 12
 
0.4%
10 9
 
0.3%
6 8
 
0.3%
12 5
 
0.2%
Other values (18) 25
 
0.8%

Length

2024-04-18T01:02:02.571402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 2583
87.7%
2 139
 
4.7%
na 66
 
2.2%
3 44
 
1.5%
2020-10-08 38
 
1.3%
4 17
 
0.6%
5 12
 
0.4%
10 9
 
0.3%
6 8
 
0.3%
12 5
 
0.2%
Other values (18) 25
 
0.8%

manager
Text

MISSING 

Distinct77
Distinct (%)2.7%
Missing66
Missing (%)2.2%
Memory size23.1 KiB
2024-04-18T01:02:02.731927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.4770833
Min length3

Characters and Unicode

Total characters27294
Distinct characters80
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.3%

Sample

1st row건설과
2nd row건설과
3rd row건설과
4th row건설과
5th row건설과
ValueCountFrequency (%)
부산광역시 842
18.6%
도시안전과 572
12.6%
건설과 315
 
6.9%
해운대구청(안전총괄과 304
 
6.7%
사상구청 279
 
6.2%
금정구(도시안전과 232
 
5.1%
주민센터 202
 
4.5%
안전총괄과 194
 
4.3%
연제구청 193
 
4.3%
북구청(도시관리과 132
 
2.9%
Other values (70) 1268
28.0%
2024-04-18T01:02:03.033924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 2021
 
7.4%
시 1836
 
6.7%
1653
 
6.1%
구 1650
 
6.0%
전 1553
 
5.7%
안 1528
 
5.6%
청 1341
 
4.9%
도 994
 
3.6%
산 914
 
3.3%
( 889
 
3.3%
Other values (70) 12915
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23008
84.3%
Space Separator 1653
 
6.1%
Open Punctuation 889
 
3.3%
Close Punctuation 889
 
3.3%
Decimal Number 813
 
3.0%
Other Punctuation 42
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 2021
 
8.8%
시 1836
 
8.0%
구 1650
 
7.2%
전 1553
 
6.7%
안 1528
 
6.6%
청 1341
 
5.8%
도 994
 
4.3%
산 914
 
4.0%
부 880
 
3.8%
광 842
 
3.7%
Other values (56) 9449
41.1%
Decimal Number
ValueCountFrequency (%)
1 268
33.0%
2 212
26.1%
3 174
21.4%
5 76
 
9.3%
4 40
 
4.9%
6 26
 
3.2%
9 7
 
0.9%
7 4
 
0.5%
0 4
 
0.5%
8 2
 
0.2%
Space Separator
ValueCountFrequency (%)
1653
100.0%
Open Punctuation
ValueCountFrequency (%)
( 889
100.0%
Close Punctuation
ValueCountFrequency (%)
) 889
100.0%
Other Punctuation
ValueCountFrequency (%)
. 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23008
84.3%
Common 4286
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 2021
 
8.8%
시 1836
 
8.0%
구 1650
 
7.2%
전 1553
 
6.7%
안 1528
 
6.6%
청 1341
 
5.8%
도 994
 
4.3%
산 914
 
4.0%
부 880
 
3.8%
광 842
 
3.7%
Other values (56) 9449
41.1%
Common
ValueCountFrequency (%)
1653
38.6%
( 889
20.7%
) 889
20.7%
1 268
 
6.3%
2 212
 
4.9%
3 174
 
4.1%
5 76
 
1.8%
. 42
 
1.0%
4 40
 
0.9%
6 26
 
0.6%
Other values (4) 17
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23008
84.3%
ASCII 4286
 
15.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 2021
 
8.8%
시 1836
 
8.0%
구 1650
 
7.2%
전 1553
 
6.7%
안 1528
 
6.6%
청 1341
 
5.8%
도 994
 
4.3%
산 914
 
4.0%
부 880
 
3.8%
광 842
 
3.7%
Other values (56) 9449
41.1%
ASCII
ValueCountFrequency (%)
1653
38.6%
( 889
20.7%
) 889
20.7%
1 268
 
6.3%
2 212
 
4.9%
3 174
 
4.1%
5 76
 
1.8%
. 42
 
1.0%
4 40
 
0.9%
6 26
 
0.6%
Other values (4) 17
 
0.4%

tel
Text

MISSING 

Distinct78
Distinct (%)2.7%
Missing66
Missing (%)2.2%
Memory size23.1 KiB
2024-04-18T01:02:03.221312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.927778
Min length6

Characters and Unicode

Total characters34352
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.6%

Sample

1st row051-220-4665
2nd row051-220-4665
3rd row051-220-4665
4th row051-220-4665
5th row051-220-4665
ValueCountFrequency (%)
051-605-4124 330
11.5%
051-220-4665 315
 
10.9%
051-749-6168 304
 
10.6%
051-310-4636 279
 
9.7%
051-519-4654 232
 
8.1%
051-607-4654 167
 
5.8%
051-309-4712 132
 
4.6%
051-610-4642 110
 
3.8%
051-240-4645 104
 
3.6%
051-419-4644 100
 
3.5%
Other values (68) 807
28.0%
2024-04-18T01:02:03.514637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5676
16.5%
5 5081
14.8%
0 4995
14.5%
1 4539
13.2%
4 4458
13.0%
6 4241
12.3%
2 1773
 
5.2%
7 1155
 
3.4%
9 1106
 
3.2%
3 866
 
2.5%
Other values (2) 462
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28634
83.4%
Dash Punctuation 5676
 
16.5%
Other Punctuation 42
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5081
17.7%
0 4995
17.4%
1 4539
15.9%
4 4458
15.6%
6 4241
14.8%
2 1773
 
6.2%
7 1155
 
4.0%
9 1106
 
3.9%
3 866
 
3.0%
8 420
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 5676
100.0%
Other Punctuation
ValueCountFrequency (%)
. 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5676
16.5%
5 5081
14.8%
0 4995
14.5%
1 4539
13.2%
4 4458
13.0%
6 4241
12.3%
2 1773
 
5.2%
7 1155
 
3.4%
9 1106
 
3.2%
3 866
 
2.5%
Other values (2) 462
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5676
16.5%
5 5081
14.8%
0 4995
14.5%
1 4539
13.2%
4 4458
13.0%
6 4241
12.3%
2 1773
 
5.2%
7 1155
 
3.4%
9 1106
 
3.2%
3 866
 
2.5%
Other values (2) 462
 
1.3%

gugun
Categorical

Distinct17
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
부산광역시 부산진구
330 
부산광역시 사하구
315 
부산광역시 해운대구
304 
부산광역시 사상구
279 
부산광역시 금정구
232 
Other values (12)
1486 

Length

Max length10
Median length9
Mean length8.8010862
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 사하구
2nd row부산광역시 사하구
3rd row부산광역시 사하구
4th row부산광역시 사하구
5th row부산광역시 사하구

Common Values

ValueCountFrequency (%)
부산광역시 부산진구 330
11.2%
부산광역시 사하구 315
10.7%
부산광역시 해운대구 304
10.3%
부산광역시 사상구 279
9.5%
부산광역시 금정구 232
 
7.9%
부산광역시 동구 202
 
6.9%
부산광역시 연제구 193
 
6.6%
부산광역시 남구 167
 
5.7%
부산광역시 동래구 151
 
5.1%
부산광역시 북구 132
 
4.5%
Other values (7) 641
21.8%

Length

2024-04-18T01:02:03.624397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 2838
49.1%
부산진구 330
 
5.7%
사하구 315
 
5.4%
해운대구 304
 
5.3%
사상구 279
 
4.8%
금정구 232
 
4.0%
동구 202
 
3.5%
연제구 193
 
3.3%
남구 167
 
2.9%
동래구 151
 
2.6%
Other values (8) 773
 
13.4%

data_day
Date

MISSING 

Distinct5
Distinct (%)0.2%
Missing66
Missing (%)2.2%
Memory size23.1 KiB
Minimum2020-04-24 00:00:00
Maximum2021-01-05 17:47:21
2024-04-18T01:02:03.724889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:02:03.812787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

lat
Real number (ℝ)

MISSING 

Distinct2193
Distinct (%)77.3%
Missing109
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean35.656716
Minimum35.019376
Maximum129.048
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.0 KiB
2024-04-18T01:02:03.918771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.019376
5-th percentile35.077313
Q135.123028
median35.158693
Q335.192287
95-th percentile35.251672
Maximum129.048
Range94.028624
Interquartile range (IQR)0.0692595

Descriptive statistics

Standard deviation6.8100059
Coefficient of variation (CV)0.19098803
Kurtosis184.42835
Mean35.656716
Median Absolute Deviation (MAD)0.034135786
Skewness13.648433
Sum101158.1
Variance46.37618
MonotonicityNot monotonic
2024-04-18T01:02:04.020692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2311994223 41
 
1.4%
35.1256321551 25
 
0.8%
35.22468838 14
 
0.5%
35.135 11
 
0.4%
35.146 10
 
0.3%
35.137 10
 
0.3%
35.2830430795 9
 
0.3%
35.136 9
 
0.3%
35.127 9
 
0.3%
35.18408371 8
 
0.3%
Other values (2183) 2691
91.3%
(Missing) 109
 
3.7%
ValueCountFrequency (%)
35.019376 2
0.1%
35.030191 2
0.1%
35.048487 2
0.1%
35.049789 2
0.1%
35.050163 2
0.1%
35.051306 2
0.1%
35.051649 2
0.1%
35.052104 2
0.1%
35.05275 2
0.1%
35.052765 2
0.1%
ValueCountFrequency (%)
129.048 1
 
< 0.1%
129.047 1
 
< 0.1%
129.046 1
 
< 0.1%
129.045 2
0.1%
129.044 2
0.1%
129.043 1
 
< 0.1%
129.042 2
0.1%
129.04 3
0.1%
129.038 2
0.1%
37.402728 1
 
< 0.1%

lng
Real number (ℝ)

MISSING 

Distinct2193
Distinct (%)77.3%
Missing109
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean128.55012
Minimum35.114
Maximum129.2823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.0 KiB
2024-04-18T01:02:04.121897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.114
5-th percentile128.96306
Q1129.00864
median129.0493
Q3129.08864
95-th percentile129.15971
Maximum129.2823
Range94.1683
Interquartile range (IQR)0.0799995

Descriptive statistics

Standard deviation6.8135324
Coefficient of variation (CV)0.053002925
Kurtosis184.38672
Mean128.55012
Median Absolute Deviation (MAD)0.0399953
Skewness-13.646169
Sum364696.69
Variance46.424223
MonotonicityNot monotonic
2024-04-18T01:02:04.224401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0757629134 41
 
1.4%
129.0878604715 25
 
0.8%
129.017144 14
 
0.5%
129.036 12
 
0.4%
129.041 12
 
0.4%
129.044 10
 
0.3%
129.046 10
 
0.3%
129.043 9
 
0.3%
129.0676212385 9
 
0.3%
129.035 9
 
0.3%
Other values (2183) 2686
91.2%
(Missing) 109
 
3.7%
ValueCountFrequency (%)
35.114 1
 
< 0.1%
35.118 1
 
< 0.1%
35.119 2
0.1%
35.12 2
0.1%
35.121 4
0.1%
35.122 2
0.1%
35.124 1
 
< 0.1%
35.125 1
 
< 0.1%
35.126 1
 
< 0.1%
126.022912 1
 
< 0.1%
ValueCountFrequency (%)
129.2823 1
< 0.1%
129.259298 1
< 0.1%
129.2592 1
< 0.1%
129.232025 1
< 0.1%
129.2142 2
0.1%
129.212348 1
< 0.1%
129.209708 1
< 0.1%
129.209138 1
< 0.1%
129.2089 1
< 0.1%
129.2018 1
< 0.1%

apr_at
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2946
Missing (%)100.0%
Memory size26.0 KiB

last_load_dttm
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing108
Missing (%)3.7%
Memory size23.1 KiB
Minimum2021-01-05 17:47:21
Maximum2021-01-05 17:47:21
2024-04-18T01:02:04.300886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:02:04.367598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T01:01:57.472651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:01:57.336112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:01:57.535161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:01:57.397973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T01:02:04.424715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
instt_codeqtymanagertelgugundata_daylatlng
instt_code1.0000.8620.9960.9981.0000.9970.3230.323
qty0.8621.0000.8410.8410.6270.7670.0000.000
manager0.9960.8411.0000.9981.0000.9971.0001.000
tel0.9980.8410.9981.0001.0000.9971.0001.000
gugun1.0000.6271.0001.0001.0000.9990.3230.323
data_day0.9970.7670.9970.9970.9991.0000.3900.390
lat0.3230.0001.0001.0000.3230.3901.0000.999
lng0.3230.0001.0001.0000.3230.3900.9991.000
2024-04-18T01:02:04.514605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
gugunqty
gugun1.0000.236
qty0.2361.000
2024-04-18T01:02:04.577078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
latlngqtygugun
lat1.0000.4730.0000.253
lng0.4731.0000.0000.253
qty0.0000.0001.0000.236
gugun0.2530.2530.2361.000

Missing values

2024-04-18T01:01:57.659060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T01:01:57.855527image/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.
2024-04-18T01:01:58.001216image/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

skeyinstt_codeadmns_nmseqspotaddr_roadaddr_jibunqtymanagertelgugundata_daylatlngapr_atlast_load_dttm
0471673340000다대2동<NA>다대종합사회복지관건너편화단부산광역시 사하구 다대로 381(다대동)부산광역시 사하구 다대동 93-31건설과051-220-4665부산광역시 사하구2020-07-3135.068722128.978583<NA>2021-01-05 17:47:21
1471683340000다대2동<NA>다대종합사회복지관 앞부산광역시 사하구 다대로 440(다대동)부산광역시 사하구 다대동 113-121건설과051-220-4665부산광역시 사하구2020-07-3135.063767128.979269<NA>2021-01-05 17:47:21
2471693340000다대2동<NA>다대로381 앞부산광역시 사하구 다대로 381(다대동)부산광역시 사하구 다대동 93-31건설과051-220-4665부산광역시 사하구2020-07-3135.068722128.978583<NA>2021-01-05 17:47:21
3471703340000구평동<NA>용화사 앞부산광역시 사하구 감천항로190번길 47-7(구평동)부산광역시 사하구 구평동 2721건설과051-220-4665부산광역시 사하구2020-07-3135.077624128.986825<NA>2021-01-05 17:47:21
4471713340000구평동<NA>두송로 155 건너편부산광역시 사하구 두송로 155(구평동)부산광역시 사하구 구평동 435-1021건설과051-220-4665부산광역시 사하구2020-07-3135.071799128.984771<NA>2021-01-05 17:47:21
5471723340000감천2동<NA>삼거리약국 회전지점부산광역시 사하구 옥천로 73-1(감천동)부산광역시 사하구 감천동 16-511건설과051-220-4665부산광역시 사하구2020-07-3135.093224129.009091<NA>2021-01-05 17:47:21
6471733340000장림1동<NA>보덕포 중구환경관리소옆, 삼영정밀앞, 배산산업앞부산광역시 사하구 보덕포1길 75(장림동)부산광역시 사하구 장림동 9353건설과051-220-4665부산광역시 사하구2020-07-3135.072952128.96132<NA>2021-01-05 17:47:21
7471743340000장림2동<NA>청야수산뒷길 (장평로83번길35)부산광역시 사하구 장평로83번길 35(장림동)부산광역시 사하구 장림동 580-11건설과051-220-4665부산광역시 사하구2020-07-3135.073416128.970953<NA>2021-01-05 17:47:21
8471753340000장림2동<NA>국제마마@앞, 벽산마마@앞부산광역시 사하구 장평로41번길 51(장림동)부산광역시 사하구 장림동 566-122건설과051-220-4665부산광역시 사하구2020-07-3135.070229128.970465<NA>2021-01-05 17:47:21
9471763340000괴정4동<NA>동덕맨션 입구 (승학로167번길)부산광역시 사하구 승학로 167(괴정동)부산광역시 사하구 괴정동 1081-11건설과051-220-4665부산광역시 사하구2020-07-3135.101582128.984712<NA>2021-01-05 17:47:21
skeyinstt_codeadmns_nmseqspotaddr_roadaddr_jibunqtymanagertelgugundata_daylatlngapr_atlast_load_dttm
2936479183270000초량1동초량1동-11홍성방 본관 앞-상해문 옆(중앙대로179번길 1)부산광역시 동구 중앙대로179번길 1부산광역시 동구 초량동 1210-11초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.113129.039<NA>2021-01-05 17:47:21
2937479193270000초량1동초량1동-12초원아파트 계단 시작하는곳(영초길 135-4)부산광역시 동구 영초길 135-4부산광역시 동구 초량동 1064-11초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.116129.034<NA>2021-01-05 17:47:21
2938479203270000초량1동초량1동-13배룡선빌리지 맨 윗길(영초길 142)부산광역시 동구 영초길 142부산광역시 동구 초량동 1064-781초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.115129.035<NA>2021-01-05 17:47:21
2939479213270000초량1동초량1동-14상해문 입구 메가커피 앞(중앙대로181)부산광역시 동구 중앙대로 181부산광역시 동구 초량동 1209-131초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.114129.039<NA>2021-01-05 17:47:21
2940479223270000초량1동초량1동-15신한은행 앞(중앙대로167)부산광역시 동구 중앙대로 167부산광역시 동구 초량동 1210-151초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.113129.038<NA>2021-01-05 17:47:21
2941479233270000초량1동초량1동-16SC제일은행 앞(중앙대로176)부산광역시 동구 중앙대로 176부산광역시 동구 초량동 1211-11초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.113129.039<NA>2021-01-05 17:47:21
2942479243270000초량1동초량1동-17교직원 공제회관 앞 (중앙대로192)부산광역시 동구 중앙대로 192부산광역시 동구 초량동 1205-11초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.114129.04<NA>2021-01-05 17:47:21
2943479253270000초량1동초량1동-18산복도로 마마맨션 계단내리막 입구(초량동994-69)<NA>부산광역시 동구 초량동 994-691초량1동 주민센터051-440-6102부산광역시 동구2020-10-0835.116129.034<NA>2021-01-05 17:47:21
2944479263270000초량2동초량2동-1하이마트 앞(중앙대로 229)부산광역시 동구 중앙대로 229부산광역시 동구 초량동 359-11초량2동 주민센터051-440-6136부산광역시 동구2020-10-0835.118129.041<NA>2021-01-05 17:47:21
2945479273270000초량2동초량2동-2북창동 순두부 앞(중앙대로221번길 1)부산광역시 동구 중앙대로221번길 1부산광역시 동구 초량동 377-31초량2동 주민센터051-440-6136부산광역시 동구2020-10-0835.117129.04<NA>2021-01-05 17:47:21

Duplicate rows

Most frequently occurring

skeyinstt_codeadmns_nmseqspotaddr_roadaddr_jibunqtymanagertelgugundata_daylatlnglast_load_dttm# duplicates
0<NA>부산광역시 동구 홍곡남로 50부산광역시 동구 수정동 1048-351수정1동 주민센터051-440-6187부산광역시 동구2020-10-0835.126129.038<NA>2021-01-05 17:47:21<NA><NA><NA>2