Overview

Dataset statistics

Number of variables9
Number of observations3559
Missing cells773
Missing cells (%)2.4%
Duplicate rows2
Duplicate rows (%)0.1%
Total size in memory260.8 KiB
Average record size in memory75.0 B

Variable types

Categorical2
Text4
Numeric3

Alerts

Dataset has 2 (0.1%) duplicate rowsDuplicates
우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
도로명주소 has 337 (9.5%) missing valuesMissing
우편번호 has 122 (3.4%) missing valuesMissing
WGS84위도 has 157 (4.4%) missing valuesMissing
WGS84경도 has 157 (4.4%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:21:53.250509
Analysis finished2023-12-10 21:21:55.529061
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
수원시
369 
성남시
289 
고양시
256 
안산시
 
209
용인시
 
189
Other values (27)
2247 

Length

Max length4
Median length3
Mean length3.0930037
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 369
 
10.4%
성남시 289
 
8.1%
고양시 256
 
7.2%
안산시 209
 
5.9%
용인시 189
 
5.3%
부천시 189
 
5.3%
파주시 184
 
5.2%
화성시 151
 
4.2%
안양시 147
 
4.1%
남양주시 141
 
4.0%
Other values (22) 1435
40.3%

Length

2023-12-11T06:21:55.596272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 369
 
10.4%
성남시 289
 
8.1%
고양시 256
 
7.2%
안산시 209
 
5.9%
용인시 189
 
5.3%
부천시 189
 
5.3%
파주시 184
 
5.2%
화성시 151
 
4.2%
안양시 147
 
4.1%
남양주시 141
 
4.0%
Other values (22) 1435
40.3%

가맹점명
Text

Distinct3374
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-11T06:21:55.841536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length7.2391121
Min length1

Characters and Unicode

Total characters25764
Distinct characters768
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3233 ?
Unique (%)90.8%

Sample

1st row(주) 남이섬
2nd row(주)광명렌트카 가평영업소
3rd row(주)꿈의동산
4th row(주)이랜드파크 켄싱턴리조트 청평
5th row(주)채움렌트카 가평영업소
ValueCountFrequency (%)
스튜디오 97
 
2.1%
주식회사 74
 
1.6%
경기 51
 
1.1%
정보화마을 51
 
1.1%
롯데시네마 34
 
0.7%
cgv 33
 
0.7%
주 31
 
0.7%
모텔 19
 
0.4%
메가박스 19
 
0.4%
주)롯데렌터카 17
 
0.4%
Other values (3648) 4217
90.8%
2023-12-11T06:21:56.261730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1105
 
4.3%
스 823
 
3.2%
) 657
 
2.6%
( 640
 
2.5%
주 590
 
2.3%
오 538
 
2.1%
사 534
 
2.1%
디 494
 
1.9%
튜 437
 
1.7%
이 412
 
1.6%
Other values (758) 19534
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22220
86.2%
Space Separator 1105
 
4.3%
Close Punctuation 659
 
2.6%
Open Punctuation 641
 
2.5%
Uppercase Letter 591
 
2.3%
Lowercase Letter 372
 
1.4%
Decimal Number 112
 
0.4%
Other Punctuation 30
 
0.1%
Other Symbol 28
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 823
 
3.7%
주 590
 
2.7%
오 538
 
2.4%
사 534
 
2.4%
디 494
 
2.2%
튜 437
 
2.0%
이 412
 
1.9%
관 412
 
1.9%
점 408
 
1.8%
텔 358
 
1.6%
Other values (682) 17214
77.5%
Uppercase Letter
ValueCountFrequency (%)
C 53
 
9.0%
G 52
 
8.8%
S 50
 
8.5%
V 40
 
6.8%
O 37
 
6.3%
E 35
 
5.9%
I 31
 
5.2%
T 29
 
4.9%
N 25
 
4.2%
D 24
 
4.1%
Other values (16) 215
36.4%
Lowercase Letter
ValueCountFrequency (%)
o 57
15.3%
e 34
 
9.1%
t 29
 
7.8%
i 28
 
7.5%
u 26
 
7.0%
a 25
 
6.7%
n 19
 
5.1%
p 16
 
4.3%
d 15
 
4.0%
l 15
 
4.0%
Other values (15) 108
29.0%
Decimal Number
ValueCountFrequency (%)
1 31
27.7%
2 25
22.3%
3 14
12.5%
7 11
 
9.8%
6 7
 
6.2%
0 7
 
6.2%
4 7
 
6.2%
9 4
 
3.6%
5 4
 
3.6%
8 2
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 15
50.0%
, 5
 
16.7%
/ 4
 
13.3%
& 4
 
13.3%
″ 2
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 657
99.7%
] 1
 
0.2%
} 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 640
99.8%
[ 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
1105
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22248
86.4%
Common 2553
 
9.9%
Latin 963
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 823
 
3.7%
주 590
 
2.7%
오 538
 
2.4%
사 534
 
2.4%
디 494
 
2.2%
튜 437
 
2.0%
이 412
 
1.9%
관 412
 
1.9%
점 408
 
1.8%
텔 358
 
1.6%
Other values (683) 17242
77.5%
Latin
ValueCountFrequency (%)
o 57
 
5.9%
C 53
 
5.5%
G 52
 
5.4%
S 50
 
5.2%
V 40
 
4.2%
O 37
 
3.8%
E 35
 
3.6%
e 34
 
3.5%
I 31
 
3.2%
t 29
 
3.0%
Other values (41) 545
56.6%
Common
ValueCountFrequency (%)
1105
43.3%
) 657
25.7%
( 640
25.1%
1 31
 
1.2%
2 25
 
1.0%
. 15
 
0.6%
3 14
 
0.5%
7 11
 
0.4%
6 7
 
0.3%
0 7
 
0.3%
Other values (14) 41
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22220
86.2%
ASCII 3514
 
13.6%
None 28
 
0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1105
31.4%
) 657
18.7%
( 640
18.2%
o 57
 
1.6%
C 53
 
1.5%
G 52
 
1.5%
S 50
 
1.4%
V 40
 
1.1%
O 37
 
1.1%
E 35
 
1.0%
Other values (64) 788
22.4%
Hangul
ValueCountFrequency (%)
스 823
 
3.7%
주 590
 
2.7%
오 538
 
2.4%
사 534
 
2.4%
디 494
 
2.2%
튜 437
 
2.0%
이 412
 
1.9%
관 412
 
1.9%
점 408
 
1.8%
텔 358
 
1.6%
Other values (682) 17214
77.5%
None
ValueCountFrequency (%)
㈜ 28
100.0%
Punctuation
ValueCountFrequency (%)
″ 2
100.0%

도로명주소
Text

MISSING 

Distinct2990
Distinct (%)92.8%
Missing337
Missing (%)9.5%
Memory size27.9 KiB
2023-12-11T06:21:56.558378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length19.432961
Min length13

Characters and Unicode

Total characters62613
Distinct characters366
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2810 ?
Unique (%)87.2%

Sample

1st row경기도 가평군 가평읍 북한강변로 1024
2nd row경기도 가평군 가평읍 오리나무길 41-20
3rd row경기도 가평군 청평면 에덴벚꽃길 189
4th row경기도 가평군 상면 청군로 430
5th row경기도 가평군 가평읍 용추로 227-98
ValueCountFrequency (%)
경기도 3217
 
21.6%
수원시 331
 
2.2%
성남시 275
 
1.8%
고양시 234
 
1.6%
안산시 191
 
1.3%
부천시 182
 
1.2%
용인시 169
 
1.1%
파주시 151
 
1.0%
화성시 140
 
0.9%
팔달구 139
 
0.9%
Other values (3017) 9897
66.3%
2023-12-11T06:21:57.041152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11704
18.7%
경 3359
 
5.4%
기 3325
 
5.3%
도 3275
 
5.2%
시 3164
 
5.1%
로 2921
 
4.7%
1 2295
 
3.7%
2 1559
 
2.5%
구 1447
 
2.3%
3 1281
 
2.0%
Other values (356) 28283
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39076
62.4%
Space Separator 11704
 
18.7%
Decimal Number 11207
 
17.9%
Dash Punctuation 624
 
1.0%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 3359
 
8.6%
기 3325
 
8.5%
도 3275
 
8.4%
시 3164
 
8.1%
로 2921
 
7.5%
구 1447
 
3.7%
길 1280
 
3.3%
번 932
 
2.4%
양 860
 
2.2%
안 768
 
2.0%
Other values (343) 17745
45.4%
Decimal Number
ValueCountFrequency (%)
1 2295
20.5%
2 1559
13.9%
3 1281
11.4%
4 1039
9.3%
5 967
8.6%
6 908
 
8.1%
7 890
 
7.9%
9 792
 
7.1%
0 752
 
6.7%
8 724
 
6.5%
Space Separator
ValueCountFrequency (%)
11704
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 624
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39076
62.4%
Common 23537
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 3359
 
8.6%
기 3325
 
8.5%
도 3275
 
8.4%
시 3164
 
8.1%
로 2921
 
7.5%
구 1447
 
3.7%
길 1280
 
3.3%
번 932
 
2.4%
양 860
 
2.2%
안 768
 
2.0%
Other values (343) 17745
45.4%
Common
ValueCountFrequency (%)
11704
49.7%
1 2295
 
9.8%
2 1559
 
6.6%
3 1281
 
5.4%
4 1039
 
4.4%
5 967
 
4.1%
6 908
 
3.9%
7 890
 
3.8%
9 792
 
3.4%
0 752
 
3.2%
Other values (3) 1350
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39076
62.4%
ASCII 23537
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11704
49.7%
1 2295
 
9.8%
2 1559
 
6.6%
3 1281
 
5.4%
4 1039
 
4.4%
5 967
 
4.1%
6 908
 
3.9%
7 890
 
3.8%
9 792
 
3.4%
0 752
 
3.2%
Other values (3) 1350
 
5.7%
Hangul
ValueCountFrequency (%)
경 3359
 
8.6%
기 3325
 
8.5%
도 3275
 
8.4%
시 3164
 
8.1%
로 2921
 
7.5%
구 1447
 
3.7%
길 1280
 
3.3%
번 932
 
2.4%
양 860
 
2.2%
안 768
 
2.0%
Other values (343) 17745
45.4%

지번주소
Text

Distinct3506
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-11T06:21:57.353615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length24.684462
Min length11

Characters and Unicode

Total characters87852
Distinct characters530
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3459 ?
Unique (%)97.2%

Sample

1st row경기도 가평군 가평읍 달전리 144-11번지
2nd row경기도 가평군 가평읍 대곡리 171-5
3rd row경기도 가평군 청평면 상천리 3번지
4th row경기도 가평군 상면 덕현리 402-10번지
5th row경기도 가평군 가평읍 달전리571
ValueCountFrequency (%)
경기도 3506
 
18.5%
수원시 369
 
1.9%
성남시 289
 
1.5%
고양시 255
 
1.3%
안산시 209
 
1.1%
용인시 189
 
1.0%
부천시 189
 
1.0%
파주시 184
 
1.0%
팔달구 159
 
0.8%
화성시 151
 
0.8%
Other values (5653) 13491
71.0%
2023-12-11T06:21:57.784574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15435
 
17.6%
1 3908
 
4.4%
기 3669
 
4.2%
경 3587
 
4.1%
도 3587
 
4.1%
시 3493
 
4.0%
동 3186
 
3.6%
- 2681
 
3.1%
2 2453
 
2.8%
지 2392
 
2.7%
Other values (520) 43461
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51614
58.8%
Decimal Number 17749
 
20.2%
Space Separator 15435
 
17.6%
Dash Punctuation 2681
 
3.1%
Uppercase Letter 173
 
0.2%
Other Punctuation 89
 
0.1%
Open Punctuation 41
 
< 0.1%
Close Punctuation 41
 
< 0.1%
Math Symbol 22
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3669
 
7.1%
경 3587
 
6.9%
도 3587
 
6.9%
시 3493
 
6.8%
동 3186
 
6.2%
지 2392
 
4.6%
번 2076
 
4.0%
구 1579
 
3.1%
양 1036
 
2.0%
리 932
 
1.8%
Other values (472) 26077
50.5%
Uppercase Letter
ValueCountFrequency (%)
B 51
29.5%
A 21
12.1%
I 13
 
7.5%
C 11
 
6.4%
T 11
 
6.4%
E 8
 
4.6%
K 7
 
4.0%
P 7
 
4.0%
O 5
 
2.9%
R 5
 
2.9%
Other values (15) 34
19.7%
Decimal Number
ValueCountFrequency (%)
1 3908
22.0%
2 2453
13.8%
3 1926
10.9%
0 1757
9.9%
4 1584
8.9%
5 1501
 
8.5%
6 1307
 
7.4%
7 1259
 
7.1%
8 1109
 
6.2%
9 945
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 75
84.3%
/ 7
 
7.9%
. 6
 
6.7%
@ 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
l 2
28.6%
f 1
 
14.3%
c 1
 
14.3%
Space Separator
ValueCountFrequency (%)
15435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2681
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51614
58.8%
Common 36058
41.0%
Latin 180
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3669
 
7.1%
경 3587
 
6.9%
도 3587
 
6.9%
시 3493
 
6.8%
동 3186
 
6.2%
지 2392
 
4.6%
번 2076
 
4.0%
구 1579
 
3.1%
양 1036
 
2.0%
리 932
 
1.8%
Other values (472) 26077
50.5%
Latin
ValueCountFrequency (%)
B 51
28.3%
A 21
11.7%
I 13
 
7.2%
C 11
 
6.1%
T 11
 
6.1%
E 8
 
4.4%
K 7
 
3.9%
P 7
 
3.9%
O 5
 
2.8%
R 5
 
2.8%
Other values (19) 41
22.8%
Common
ValueCountFrequency (%)
15435
42.8%
1 3908
 
10.8%
- 2681
 
7.4%
2 2453
 
6.8%
3 1926
 
5.3%
0 1757
 
4.9%
4 1584
 
4.4%
5 1501
 
4.2%
6 1307
 
3.6%
7 1259
 
3.5%
Other values (9) 2247
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51614
58.8%
ASCII 36238
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15435
42.6%
1 3908
 
10.8%
- 2681
 
7.4%
2 2453
 
6.8%
3 1926
 
5.3%
0 1757
 
4.8%
4 1584
 
4.4%
5 1501
 
4.1%
6 1307
 
3.6%
7 1259
 
3.5%
Other values (38) 2427
 
6.7%
Hangul
ValueCountFrequency (%)
기 3669
 
7.1%
경 3587
 
6.9%
도 3587
 
6.9%
시 3493
 
6.8%
동 3186
 
6.2%
지 2392
 
4.6%
번 2076
 
4.0%
구 1579
 
3.1%
양 1036
 
2.0%
리 932
 
1.8%
Other values (472) 26077
50.5%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1733
Distinct (%)50.4%
Missing122
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean14083.974
Minimum10005
Maximum22636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-11T06:21:57.981158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10005
5-th percentile10386
Q111922
median14001
Q316443
95-th percentile18137
Maximum22636
Range12631
Interquartile range (IQR)4521

Descriptive statistics

Standard deviation2529.5911
Coefficient of variation (CV)0.17960777
Kurtosis-1.1388667
Mean14083.974
Median Absolute Deviation (MAD)2306
Skewness0.12989476
Sum48406618
Variance6398831.3
MonotonicityNot monotonic
2023-12-11T06:21:58.293947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10859 30
 
0.8%
13246 21
 
0.6%
10881 17
 
0.5%
11692 16
 
0.4%
13992 15
 
0.4%
16455 15
 
0.4%
15865 14
 
0.4%
15361 14
 
0.4%
10500 12
 
0.3%
17308 12
 
0.3%
Other values (1723) 3271
91.9%
(Missing) 122
 
3.4%
ValueCountFrequency (%)
10005 1
 
< 0.1%
10010 1
 
< 0.1%
10011 1
 
< 0.1%
10012 1
 
< 0.1%
10013 1
 
< 0.1%
10018 6
0.2%
10021 1
 
< 0.1%
10029 1
 
< 0.1%
10039 2
 
0.1%
10041 1
 
< 0.1%
ValueCountFrequency (%)
22636 1
 
< 0.1%
22554 1
 
< 0.1%
22228 1
 
< 0.1%
21507 1
 
< 0.1%
21438 1
 
< 0.1%
18635 1
 
< 0.1%
18625 1
 
< 0.1%
18611 1
 
< 0.1%
18600 5
0.1%
18597 1
 
< 0.1%

전화번호
Text

Distinct3277
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-11T06:21:58.501025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length11.871593
Min length1

Characters and Unicode

Total characters42251
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3218 ?
Unique (%)90.4%

Sample

1st row031-581-2192
2nd row031-582-5300
3rd row031-581-0515
4th row031-584 -9380
5th row031-581-1838
ValueCountFrequency (%)
1544-7788 50
 
1.4%
1544-8855 34
 
1.0%
02-1544-1122 33
 
0.9%
010 32
 
0.9%
1644-2992 28
 
0.8%
1544-0070 19
 
0.5%
02-2088-2635 18
 
0.5%
1544-1900 10
 
0.3%
1588-7890 9
 
0.3%
1577-7766 4
 
0.1%
Other values (3270) 3326
93.3%
2023-12-11T06:21:58.834794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6899
16.3%
0 6029
14.3%
1 5324
12.6%
3 5320
12.6%
2 3055
7.2%
5 2831
6.7%
7 2807
6.6%
4 2722
 
6.4%
8 2678
 
6.3%
6 2264
 
5.4%
Other values (4) 2322
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35050
83.0%
Dash Punctuation 6899
 
16.3%
Other Punctuation 285
 
0.7%
Space Separator 11
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6029
17.2%
1 5324
15.2%
3 5320
15.2%
2 3055
8.7%
5 2831
8.1%
7 2807
8.0%
4 2722
7.8%
8 2678
7.6%
6 2264
 
6.5%
9 2020
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 6899
100.0%
Other Punctuation
ValueCountFrequency (%)
* 285
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 6899
16.3%
0 6029
14.3%
1 5324
12.6%
3 5320
12.6%
2 3055
7.2%
5 2831
6.7%
7 2807
6.6%
4 2722
 
6.4%
8 2678
 
6.3%
6 2264
 
5.4%
Other values (4) 2322
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6899
16.3%
0 6029
14.3%
1 5324
12.6%
3 5320
12.6%
2 3055
7.2%
5 2831
6.7%
7 2807
6.6%
4 2722
 
6.4%
8 2678
 
6.3%
6 2264
 
5.4%
Other values (4) 2322
 
5.5%

장르
Categorical

Distinct14
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
문화일반
1114 
숙박
695 
도서
626 
항공/여객/고속버스/렌터카
233 
여행사
210 
Other values (9)
681 

Length

Max length14
Median length7
Mean length3.6344479
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관광지
2nd row항공/여객/고속버스/렌터카
3rd row테마파크/레져
4th row숙박
5th row항공/여객/고속버스/렌터카

Common Values

ValueCountFrequency (%)
문화일반 1114
31.3%
숙박 695
19.5%
도서 626
17.6%
항공/여객/고속버스/렌터카 233
 
6.5%
여행사 210
 
5.9%
관광지 137
 
3.8%
문화체험 111
 
3.1%
영화 104
 
2.9%
공연 95
 
2.7%
전시 86
 
2.4%
Other values (4) 148
 
4.2%

Length

2023-12-11T06:21:58.953360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문화일반 1114
31.3%
숙박 695
19.5%
도서 626
17.6%
항공/여객/고속버스/렌터카 233
 
6.5%
여행사 210
 
5.9%
관광지 137
 
3.8%
문화체험 111
 
3.1%
영화 104
 
2.9%
공연 95
 
2.7%
전시 86
 
2.4%
Other values (4) 148
 
4.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3167
Distinct (%)93.1%
Missing157
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean37.459784
Minimum36.916271
Maximum38.213509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-11T06:21:59.068638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.916271
5-th percentile37.092238
Q137.288572
median37.415535
Q337.651484
95-th percentile37.857327
Maximum38.213509
Range1.2972377
Interquartile range (IQR)0.36291163

Descriptive statistics

Standard deviation0.23320609
Coefficient of variation (CV)0.0062255055
Kurtosis-0.34745399
Mean37.459784
Median Absolute Deviation (MAD)0.14904117
Skewness0.32148603
Sum127438.19
Variance0.054385082
MonotonicityNot monotonic
2023-12-11T06:21:59.251368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6613265499 6
 
0.2%
37.6431934574 5
 
0.1%
37.5086718515 5
 
0.1%
37.2773344789 5
 
0.1%
37.325870193 4
 
0.1%
37.2609194665 4
 
0.1%
37.2504974396 4
 
0.1%
37.3889401776 4
 
0.1%
37.4095555385 4
 
0.1%
37.5041752477 4
 
0.1%
Other values (3157) 3357
94.3%
(Missing) 157
 
4.4%
ValueCountFrequency (%)
36.9162708577 1
< 0.1%
36.946817637 1
< 0.1%
36.9487628426 1
< 0.1%
36.9555638558 1
< 0.1%
36.9573612605 1
< 0.1%
36.9574540081 1
< 0.1%
36.9615159587 1
< 0.1%
36.9641193413 1
< 0.1%
36.9645891437 1
< 0.1%
36.9723209405 1
< 0.1%
ValueCountFrequency (%)
38.2135085751 1
< 0.1%
38.2119895078 1
< 0.1%
38.1846646709 1
< 0.1%
38.1846506888 1
< 0.1%
38.157677414 1
< 0.1%
38.1398873332 1
< 0.1%
38.1321615106 1
< 0.1%
38.1259785955 1
< 0.1%
38.1071229181 1
< 0.1%
38.1016023516 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3167
Distinct (%)93.1%
Missing157
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean127.02856
Minimum126.54764
Maximum127.7818
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-11T06:21:59.371961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54764
5-th percentile126.71907
Q1126.83683
median127.03468
Q3127.14148
95-th percentile127.4746
Maximum127.7818
Range1.2341646
Interquartile range (IQR)0.30465154

Descriptive statistics

Standard deviation0.22592769
Coefficient of variation (CV)0.0017785583
Kurtosis0.16742766
Mean127.02856
Median Absolute Deviation (MAD)0.1552661
Skewness0.60362259
Sum432151.16
Variance0.051043323
MonotonicityNot monotonic
2023-12-11T06:21:59.773643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7688109747 6
 
0.2%
126.7897203592 5
 
0.1%
126.7437361036 5
 
0.1%
127.4471528681 5
 
0.1%
127.1059037739 4
 
0.1%
127.1208130464 4
 
0.1%
127.0208246964 4
 
0.1%
127.122552825 4
 
0.1%
127.2612452109 4
 
0.1%
126.7566905848 4
 
0.1%
Other values (3157) 3357
94.3%
(Missing) 157
 
4.4%
ValueCountFrequency (%)
126.547640313 1
< 0.1%
126.5522797507 1
< 0.1%
126.5532448347 1
< 0.1%
126.5534089947 1
< 0.1%
126.5537915902 1
< 0.1%
126.5554372512 1
< 0.1%
126.5600822374 1
< 0.1%
126.5603793241 1
< 0.1%
126.5697714476 1
< 0.1%
126.5731164837 1
< 0.1%
ValueCountFrequency (%)
127.7818048877 1
< 0.1%
127.775065459 1
< 0.1%
127.754486695 1
< 0.1%
127.7405249855 1
< 0.1%
127.7373299931 1
< 0.1%
127.7188320391 1
< 0.1%
127.7125491928 1
< 0.1%
127.7024979266 1
< 0.1%
127.7007674304 1
< 0.1%
127.699168526 1
< 0.1%

Interactions

2023-12-11T06:21:54.922329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.361947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.646183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:55.021063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.468700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.744535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:55.113326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.554619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:54.828343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:21:59.887191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명우편번호장르WGS84위도WGS84경도
시군명1.0000.9930.3870.9580.930
우편번호0.9931.0000.1920.8060.656
장르0.3870.1921.0000.2720.258
WGS84위도0.9580.8060.2721.0000.612
WGS84경도0.9300.6560.2580.6121.000
2023-12-11T06:22:00.002052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명장르
시군명1.0000.127
장르0.1271.000
2023-12-11T06:22:00.118564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호WGS84위도WGS84경도시군명장르
우편번호1.000-0.9080.1540.9560.085
WGS84위도-0.9081.000-0.1400.7610.113
WGS84경도0.154-0.1401.0000.6710.106
시군명0.9560.7610.6711.0000.127
장르0.0850.1130.1060.1271.000

Missing values

2023-12-11T06:21:55.230059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:21:55.351471image/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.
2023-12-11T06:21:55.453637image/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

시군명가맹점명도로명주소지번주소우편번호전화번호장르WGS84위도WGS84경도
0가평군(주) 남이섬경기도 가평군 가평읍 북한강변로 1024경기도 가평군 가평읍 달전리 144-11번지12422031-581-2192관광지37.803945127.525355
1가평군(주)광명렌트카 가평영업소경기도 가평군 가평읍 오리나무길 41-20경기도 가평군 가평읍 대곡리 171-512420031-582-5300항공/여객/고속버스/렌터카37.824164127.514624
2가평군(주)꿈의동산경기도 가평군 청평면 에덴벚꽃길 189경기도 가평군 청평면 상천리 3번지12449031-581-0515테마파크/레져37.783334127.48376
3가평군(주)이랜드파크 켄싱턴리조트 청평경기도 가평군 상면 청군로 430경기도 가평군 상면 덕현리 402-10번지12446031-584 -9380숙박37.759926127.395473
4가평군(주)채움렌트카 가평영업소<NA>경기도 가평군 가평읍 달전리57112423031-581-1838항공/여객/고속버스/렌터카37.813652127.510639
5가평군G.O.M.E.T 263 (고멧263)경기도 가평군 가평읍 용추로 227-98경기도 가평군 가평읍 승안리 263-2번지12408031-582-3685숙박37.844813127.486747
6가평군SKY호텔.펜션경기도 가평군 설악면 유명로 1746-10경기도 가평군 설악면 선촌리 408-1번지12466031-585-1111숙박37.676074127.477399
7가평군가평 터미널경기도 가평군 가평읍 가화로 51경기도 가평군 가평읍 대곡리 168-9번지124201644-2992항공/여객/고속버스/렌터카37.824578127.515476
8가평군가평17분칼라경기도 가평군 가평읍 가화로 90경기도 가평군 가평읍 읍내리 475-3412419031-582-2973문화일반37.827787127.514738
9가평군가평여행경기도 가평군 북면 화악산로 729-42경기도 가평군 북면 화악리 707-1번지 가평여행펜션12402031-582-5583숙박37.933183127.554815
시군명가맹점명도로명주소지번주소우편번호전화번호장르WGS84위도WGS84경도
3549화성시화성아트홀경기도 화성시 태안로 145경기도 화성시 병점동 734번지18372031-267-8872공연37.202962127.033262
3550화성시히든스튜디오경기도 화성시 동탄공원로3길 40-8경기도 화성시 반송동 47-4번지 102호18435031-8003-7176문화일반37.207941127.062521
3551화성시힐링온천텔경기도 화성시 팔탄면 버들로1597번길 11경기도 화성시 팔탄면 월문리 235-11번지18577031-354-2262숙박37.114992126.876187
3552<NA>고원사진관인천광역시 동구 금곡로 11인천광역시 동구 금곡동 14-1번지22554032-773-3677문화일반37.472706126.6369
3553<NA>광릉경기도 남양주시 진접읍 광릉수목원로 354경기도 남양주시 진접읍 부평리 247번지12001031-527-7105관광지37.749135127.176193
3554<NA>롯데시네마 검단인천광역시 서구 완정로 163인천광역시 서구 왕길동 662-1번지 트리플타워 아울렛226361544-8855영화37.601705126.658114
3555<NA>아이풍경인천광역시 미추홀구 경원대로 749인천광역시 미추홀구 주안8동 1530-13 근화 빌딩22228032-435-7844문화일반37.44959126.689612
3556<NA>알라딘 중고서점 일산지점<NA>경기 일산시 동구 장항동 769-2 류비튜스데이 3,4,5층<NA>1544-2556도서<NA><NA>
3557<NA>역전스튜디오인천광역시 부평구 동암남로 9인천광역시 부평구 십정동 514-13번지21438032-424-3228문화일반37.471018126.70467
3558<NA>예작스튜디오인천광역시 남동구 예술로362번길 19인천광역시 남동구 간석3동 255-2청산빌딩21507032-446-5757문화일반37.46658126.704062

Duplicate rows

Most frequently occurring

시군명가맹점명도로명주소지번주소우편번호전화번호장르WGS84위도WGS84경도# duplicates
0과천시북마트경기도 과천시 새술막길 10-17경기도 과천시 중앙동 40-7번지 행진빌딩 지하1층1380702-3679-8807도서37.428712126.9911972
1김포시고려문고경기도 김포시 통진읍 조강로 37경기도 김포시 통진읍 마송리 63-11번지10018031-988-0094도서37.689504126.6009122