Overview

Dataset statistics

Number of variables8
Number of observations1442
Missing cells992
Missing cells (%)8.6%
Duplicate rows8
Duplicate rows (%)0.6%
Total size in memory94.5 KiB
Average record size in memory67.1 B

Variable types

Categorical1
Text4
Numeric3

Dataset

Description반려동물 등록대행업체 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=FD37CI7UL6TCGFW1US9028574467&infSeq=1

Alerts

Dataset has 8 (0.6%) 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 348 (24.1%) missing valuesMissing
우편번호 has 94 (6.5%) missing valuesMissing
WGS84위도 has 275 (19.1%) missing valuesMissing
WGS84경도 has 275 (19.1%) missing valuesMissing

Reproduction

Analysis started2024-05-10 20:38:00.957573
Analysis finished2024-05-10 20:38:06.179604
Duration5.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
수원시
147 
성남시
146 
고양시
129 
용인시
123 
부천시
90 
Other values (26)
807 

Length

Max length4
Median length3
Mean length3.0811373
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 147
 
10.2%
성남시 146
 
10.1%
고양시 129
 
8.9%
용인시 123
 
8.5%
부천시 90
 
6.2%
화성시 89
 
6.2%
남양주시 67
 
4.6%
김포시 64
 
4.4%
안산시 57
 
4.0%
평택시 51
 
3.5%
Other values (21) 479
33.2%

Length

2024-05-10T20:38:06.402157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 147
 
10.2%
성남시 146
 
10.1%
고양시 129
 
8.9%
용인시 123
 
8.5%
부천시 90
 
6.2%
화성시 89
 
6.2%
남양주시 67
 
4.6%
김포시 64
 
4.4%
안산시 57
 
4.0%
평택시 51
 
3.5%
Other values (21) 479
33.2%

업체명
Text

Distinct1269
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
2024-05-10T20:38:06.887909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length8.3203883
Min length2

Characters and Unicode

Total characters11998
Distinct characters526
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

Unique1182 ?
Unique (%)82.0%

Sample

1st row가평동물병원
2nd row가평축산농협 동물병원
3rd row경기 동물병원
4th row선진가축병원(산업동물출장진료전문병원)
5th row설악동물병원
ValueCountFrequency (%)
동물병원 188
 
9.8%
동물의료센터 19
 
1.0%
24시 16
 
0.8%
강아지 16
 
0.8%
한국동물구조관리협회 12
 
0.6%
동물메디컬센터 10
 
0.5%
사단)한국동물구조관리협회 9
 
0.5%
쿨펫동물병원 9
 
0.5%
현대동물병원 7
 
0.4%
주)코스모스이펙트 7
 
0.4%
Other values (1386) 1631
84.8%
2024-05-10T20:38:07.783878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1281
 
10.7%
물 1245
 
10.4%
원 1112
 
9.3%
병 1038
 
8.7%
484
 
4.0%
( 217
 
1.8%
) 217
 
1.8%
터 179
 
1.5%
센 173
 
1.4%
의 138
 
1.2%
Other values (516) 5914
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10707
89.2%
Space Separator 484
 
4.0%
Open Punctuation 217
 
1.8%
Close Punctuation 217
 
1.8%
Decimal Number 138
 
1.2%
Uppercase Letter 132
 
1.1%
Lowercase Letter 71
 
0.6%
Other Punctuation 29
 
0.2%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1281
 
12.0%
물 1245
 
11.6%
원 1112
 
10.4%
병 1038
 
9.7%
터 179
 
1.7%
센 173
 
1.6%
의 138
 
1.3%
스 135
 
1.3%
리 133
 
1.2%
이 133
 
1.2%
Other values (456) 5140
48.0%
Uppercase Letter
ValueCountFrequency (%)
A 21
15.9%
H 12
 
9.1%
E 11
 
8.3%
S 10
 
7.6%
T 9
 
6.8%
D 8
 
6.1%
P 8
 
6.1%
O 6
 
4.5%
N 6
 
4.5%
K 6
 
4.5%
Other values (14) 35
26.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
19.7%
o 8
11.3%
r 6
8.5%
t 6
8.5%
i 6
8.5%
l 5
 
7.0%
n 4
 
5.6%
s 3
 
4.2%
g 3
 
4.2%
d 3
 
4.2%
Other values (9) 13
18.3%
Decimal Number
ValueCountFrequency (%)
2 57
41.3%
4 53
38.4%
5 11
 
8.0%
3 7
 
5.1%
6 7
 
5.1%
8 2
 
1.4%
1 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 16
55.2%
& 6
 
20.7%
. 6
 
20.7%
! 1
 
3.4%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
＋ 1
50.0%
Space Separator
ValueCountFrequency (%)
484
100.0%
Open Punctuation
ValueCountFrequency (%)
( 217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10706
89.2%
Common 1088
 
9.1%
Latin 203
 
1.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1281
 
12.0%
물 1245
 
11.6%
원 1112
 
10.4%
병 1038
 
9.7%
터 179
 
1.7%
센 173
 
1.6%
의 138
 
1.3%
스 135
 
1.3%
리 133
 
1.2%
이 133
 
1.2%
Other values (455) 5139
48.0%
Latin
ValueCountFrequency (%)
A 21
 
10.3%
e 14
 
6.9%
H 12
 
5.9%
E 11
 
5.4%
S 10
 
4.9%
T 9
 
4.4%
D 8
 
3.9%
o 8
 
3.9%
P 8
 
3.9%
O 6
 
3.0%
Other values (33) 96
47.3%
Common
ValueCountFrequency (%)
484
44.5%
( 217
19.9%
) 217
19.9%
2 57
 
5.2%
4 53
 
4.9%
, 16
 
1.5%
5 11
 
1.0%
3 7
 
0.6%
6 7
 
0.6%
& 6
 
0.6%
Other values (7) 13
 
1.2%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10706
89.2%
ASCII 1290
 
10.8%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1281
 
12.0%
물 1245
 
11.6%
원 1112
 
10.4%
병 1038
 
9.7%
터 179
 
1.7%
센 173
 
1.6%
의 138
 
1.3%
스 135
 
1.3%
리 133
 
1.2%
이 133
 
1.2%
Other values (455) 5139
48.0%
ASCII
ValueCountFrequency (%)
484
37.5%
( 217
16.8%
) 217
16.8%
2 57
 
4.4%
4 53
 
4.1%
A 21
 
1.6%
, 16
 
1.2%
e 14
 
1.1%
H 12
 
0.9%
5 11
 
0.9%
Other values (49) 188
 
14.6%
CJK
ValueCountFrequency (%)
愛 1
100.0%
None
ValueCountFrequency (%)
＋ 1
100.0%

도로명주소
Text

MISSING 

Distinct1025
Distinct (%)93.7%
Missing348
Missing (%)24.1%
Memory size11.4 KiB
2024-05-10T20:38:08.388961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length19.346435
Min length13

Characters and Unicode

Total characters21165
Distinct characters297
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

Unique986 ?
Unique (%)90.1%

Sample

1st row경기도 가평군 청평면 청평중앙로 8
2nd row경기도 가평군 가평읍 향교로 4
3rd row경기도 가평군 가평읍 가화로 55-12
4th row경기도 가평군 청평면 청평중앙로 55-1
5th row경기도 고양시 일산서구 가좌1로 8
ValueCountFrequency (%)
경기도 1094
 
21.4%
성남시 119
 
2.3%
고양시 118
 
2.3%
수원시 104
 
2.0%
용인시 89
 
1.7%
부천시 81
 
1.6%
분당구 64
 
1.3%
화성시 64
 
1.3%
김포시 56
 
1.1%
원미구 55
 
1.1%
Other values (1293) 3258
63.9%
2024-05-10T20:38:09.507233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4008
18.9%
경 1149
 
5.4%
기 1142
 
5.4%
시 1138
 
5.4%
도 1118
 
5.3%
로 1053
 
5.0%
1 723
 
3.4%
구 642
 
3.0%
2 511
 
2.4%
3 452
 
2.1%
Other values (287) 9229
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13357
63.1%
Space Separator 4008
 
18.9%
Decimal Number 3628
 
17.1%
Dash Punctuation 170
 
0.8%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1149
 
8.6%
기 1142
 
8.5%
시 1138
 
8.5%
도 1118
 
8.4%
로 1053
 
7.9%
구 642
 
4.8%
양 338
 
2.5%
길 302
 
2.3%
남 269
 
2.0%
원 247
 
1.8%
Other values (274) 5959
44.6%
Decimal Number
ValueCountFrequency (%)
1 723
19.9%
2 511
14.1%
3 452
12.5%
5 327
9.0%
7 312
8.6%
4 310
8.5%
6 266
 
7.3%
8 263
 
7.2%
0 248
 
6.8%
9 216
 
6.0%
Space Separator
ValueCountFrequency (%)
4008
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13357
63.1%
Common 7808
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1149
 
8.6%
기 1142
 
8.5%
시 1138
 
8.5%
도 1118
 
8.4%
로 1053
 
7.9%
구 642
 
4.8%
양 338
 
2.5%
길 302
 
2.3%
남 269
 
2.0%
원 247
 
1.8%
Other values (274) 5959
44.6%
Common
ValueCountFrequency (%)
4008
51.3%
1 723
 
9.3%
2 511
 
6.5%
3 452
 
5.8%
5 327
 
4.2%
7 312
 
4.0%
4 310
 
4.0%
6 266
 
3.4%
8 263
 
3.4%
0 248
 
3.2%
Other values (3) 388
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13357
63.1%
ASCII 7808
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4008
51.3%
1 723
 
9.3%
2 511
 
6.5%
3 452
 
5.8%
5 327
 
4.2%
7 312
 
4.0%
4 310
 
4.0%
6 266
 
3.4%
8 263
 
3.4%
0 248
 
3.2%
Other values (3) 388
 
5.0%
Hangul
ValueCountFrequency (%)
경 1149
 
8.6%
기 1142
 
8.5%
시 1138
 
8.5%
도 1118
 
8.4%
로 1053
 
7.9%
구 642
 
4.8%
양 338
 
2.5%
길 302
 
2.3%
남 269
 
2.0%
원 247
 
1.8%
Other values (274) 5959
44.6%

지번주소
Text

Distinct1401
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
2024-05-10T20:38:10.192685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length26.903606
Min length11

Characters and Unicode

Total characters38795
Distinct characters480
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1382 ?
Unique (%)95.8%

Sample

1st row경기도 가평군 가평읍 읍내리 457번지 5호
2nd row경기도 가평군 가평읍 대곡리
3rd row경기도 가평군 청평면 청평리 438-23번지 경기동물병원
4th row경기도 가평군 가평읍 읍내리 535번지 2호
5th row경기도 가평군 설악면 신천리 454번지 3호
ValueCountFrequency (%)
경기도 1443
 
16.7%
수원시 147
 
1.7%
성남시 146
 
1.7%
고양시 131
 
1.5%
1층 126
 
1.5%
용인시 124
 
1.4%
1호 113
 
1.3%
2호 104
 
1.2%
부천시 90
 
1.0%
화성시 89
 
1.0%
Other values (2479) 6141
71.0%
2024-05-10T20:38:11.442693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7213
 
18.6%
1 1785
 
4.6%
기 1520
 
3.9%
지 1507
 
3.9%
시 1498
 
3.9%
동 1491
 
3.8%
도 1478
 
3.8%
경 1454
 
3.7%
번 1353
 
3.5%
호 967
 
2.5%
Other values (470) 18529
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23395
60.3%
Decimal Number 7401
 
19.1%
Space Separator 7213
 
18.6%
Dash Punctuation 486
 
1.3%
Uppercase Letter 121
 
0.3%
Other Punctuation 99
 
0.3%
Lowercase Letter 26
 
0.1%
Close Punctuation 19
 
< 0.1%
Open Punctuation 18
 
< 0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1520
 
6.5%
지 1507
 
6.4%
시 1498
 
6.4%
동 1491
 
6.4%
도 1478
 
6.3%
경 1454
 
6.2%
번 1353
 
5.8%
호 967
 
4.1%
구 823
 
3.5%
양 444
 
1.9%
Other values (412) 10860
46.4%
Uppercase Letter
ValueCountFrequency (%)
B 25
20.7%
A 14
11.6%
S 13
10.7%
I 8
 
6.6%
C 8
 
6.6%
E 8
 
6.6%
K 8
 
6.6%
W 5
 
4.1%
L 4
 
3.3%
G 4
 
3.3%
Other values (15) 24
19.8%
Lowercase Letter
ValueCountFrequency (%)
e 7
26.9%
m 2
 
7.7%
c 2
 
7.7%
a 2
 
7.7%
w 2
 
7.7%
t 2
 
7.7%
l 2
 
7.7%
r 1
 
3.8%
o 1
 
3.8%
s 1
 
3.8%
Other values (4) 4
15.4%
Decimal Number
ValueCountFrequency (%)
1 1785
24.1%
2 966
13.1%
0 792
10.7%
3 688
 
9.3%
4 618
 
8.4%
5 609
 
8.2%
6 548
 
7.4%
7 524
 
7.1%
8 444
 
6.0%
9 427
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 90
90.9%
. 6
 
6.1%
/ 3
 
3.0%
Space Separator
ValueCountFrequency (%)
7213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 486
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23395
60.3%
Common 15251
39.3%
Latin 149
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1520
 
6.5%
지 1507
 
6.4%
시 1498
 
6.4%
동 1491
 
6.4%
도 1478
 
6.3%
경 1454
 
6.2%
번 1353
 
5.8%
호 967
 
4.1%
구 823
 
3.5%
양 444
 
1.9%
Other values (412) 10860
46.4%
Latin
ValueCountFrequency (%)
B 25
16.8%
A 14
 
9.4%
S 13
 
8.7%
I 8
 
5.4%
C 8
 
5.4%
E 8
 
5.4%
K 8
 
5.4%
e 7
 
4.7%
W 5
 
3.4%
L 4
 
2.7%
Other values (30) 49
32.9%
Common
ValueCountFrequency (%)
7213
47.3%
1 1785
 
11.7%
2 966
 
6.3%
0 792
 
5.2%
3 688
 
4.5%
4 618
 
4.1%
5 609
 
4.0%
6 548
 
3.6%
7 524
 
3.4%
- 486
 
3.2%
Other values (8) 1022
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23395
60.3%
ASCII 15398
39.7%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7213
46.8%
1 1785
 
11.6%
2 966
 
6.3%
0 792
 
5.1%
3 688
 
4.5%
4 618
 
4.0%
5 609
 
4.0%
6 548
 
3.6%
7 524
 
3.4%
- 486
 
3.2%
Other values (47) 1169
 
7.6%
Hangul
ValueCountFrequency (%)
기 1520
 
6.5%
지 1507
 
6.4%
시 1498
 
6.4%
동 1491
 
6.4%
도 1478
 
6.3%
경 1454
 
6.2%
번 1353
 
5.8%
호 967
 
4.1%
구 823
 
3.5%
양 444
 
1.9%
Other values (412) 10860
46.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct948
Distinct (%)70.3%
Missing94
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean14129.765
Minimum10016
Maximum18630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2024-05-10T20:38:11.813027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10016
5-th percentile10233.35
Q111935.75
median13973
Q316507
95-th percentile18309
Maximum18630
Range8614
Interquartile range (IQR)4571.25

Descriptive statistics

Standard deviation2585.5729
Coefficient of variation (CV)0.18298768
Kurtosis-1.2028729
Mean14129.765
Median Absolute Deviation (MAD)2337
Skewness0.036472068
Sum19046923
Variance6685187
MonotonicityNot monotonic
2024-05-10T20:38:12.181847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11409 26
 
1.8%
10071 9
 
0.6%
15301 7
 
0.5%
15011 7
 
0.5%
16506 6
 
0.4%
13640 6
 
0.4%
12913 6
 
0.4%
11813 5
 
0.3%
10401 5
 
0.3%
14548 5
 
0.3%
Other values (938) 1266
87.8%
(Missing) 94
 
6.5%
ValueCountFrequency (%)
10016 1
 
0.1%
10018 1
 
0.1%
10019 1
 
0.1%
10036 1
 
0.1%
10042 1
 
0.1%
10056 1
 
0.1%
10059 1
 
0.1%
10060 1
 
0.1%
10064 1
 
0.1%
10068 4
0.3%
ValueCountFrequency (%)
18630 1
0.1%
18606 1
0.1%
18602 1
0.1%
18593 1
0.1%
18592 1
0.1%
18591 1
0.1%
18567 1
0.1%
18566 1
0.1%
18550 2
0.1%
18542 1
0.1%

전화번호
Text

Distinct1232
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
2024-05-10T20:38:12.694574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.942441
Min length9

Characters and Unicode

Total characters17221
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

Unique1194 ?
Unique (%)82.8%

Sample

1st row031-582-7582
2nd row031-582-4111
3rd row031-584-1282
4th row070-8739-6388
5th row031-584-3063
ValueCountFrequency (%)
146
 
10.1%
031-867-9119 24
 
1.7%
031-296-0124 8
 
0.6%
031-335-7578 2
 
0.1%
031-334-7580 2
 
0.1%
031-203-8277 2
 
0.1%
031-741-8119 2
 
0.1%
02-2038-8602 2
 
0.1%
031-848-8575 2
 
0.1%
070-8870-8245 2
 
0.1%
Other values (1222) 1250
86.7%
2024-05-10T20:38:13.692325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2591
15.0%
0 2094
12.2%
3 1980
11.5%
1 1940
11.3%
* 1606
9.3%
7 1483
8.6%
5 1411
8.2%
2 1109
6.4%
8 1001
 
5.8%
9 820
 
4.8%
Other values (2) 1186
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13024
75.6%
Dash Punctuation 2591
 
15.0%
Other Punctuation 1606
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2094
16.1%
3 1980
15.2%
1 1940
14.9%
7 1483
11.4%
5 1411
10.8%
2 1109
8.5%
8 1001
7.7%
9 820
 
6.3%
6 624
 
4.8%
4 562
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 2591
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1606
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17221
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2591
15.0%
0 2094
12.2%
3 1980
11.5%
1 1940
11.3%
* 1606
9.3%
7 1483
8.6%
5 1411
8.2%
2 1109
6.4%
8 1001
 
5.8%
9 820
 
4.8%
Other values (2) 1186
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2591
15.0%
0 2094
12.2%
3 1980
11.5%
1 1940
11.3%
* 1606
9.3%
7 1483
8.6%
5 1411
8.2%
2 1109
6.4%
8 1001
 
5.8%
9 820
 
4.8%
Other values (2) 1186
6.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1098
Distinct (%)94.1%
Missing275
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean37.452094
Minimum36.959158
Maximum38.024717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2024-05-10T20:38:14.106474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.959158
5-th percentile37.170452
Q137.30235
median37.428822
Q337.633526
95-th percentile37.745799
Maximum38.024717
Range1.0655596
Interquartile range (IQR)0.33117549

Descriptive statistics

Standard deviation0.19637092
Coefficient of variation (CV)0.005243256
Kurtosis-0.48706175
Mean37.452094
Median Absolute Deviation (MAD)0.15022053
Skewness0.099611438
Sum43706.594
Variance0.038561538
MonotonicityNot monotonic
2024-05-10T20:38:14.523941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.8701165776 24
 
1.7%
37.340253878 7
 
0.5%
37.4734793704 3
 
0.2%
37.6131390076 3
 
0.2%
37.6694732913 3
 
0.2%
37.3681926149 2
 
0.1%
37.6388182315 2
 
0.1%
37.4975212004 2
 
0.1%
37.5872006945 2
 
0.1%
37.2767142427 2
 
0.1%
Other values (1088) 1117
77.5%
(Missing) 275
 
19.1%
ValueCountFrequency (%)
36.9591575959 1
0.1%
36.9848037498 1
0.1%
36.9883452543 1
0.1%
36.988499113 1
0.1%
36.9892638565 1
0.1%
36.9927650474 1
0.1%
36.9928630371 1
0.1%
36.9929455977 1
0.1%
36.9945235041 1
0.1%
36.9954502664 1
0.1%
ValueCountFrequency (%)
38.0247171958 1
 
0.1%
38.0236410178 1
 
0.1%
37.8982669333 1
 
0.1%
37.8949907457 1
 
0.1%
37.8933923469 1
 
0.1%
37.8931053998 1
 
0.1%
37.8808927551 1
 
0.1%
37.8710629163 1
 
0.1%
37.8701165776 24
1.7%
37.8697363281 1
 
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1098
Distinct (%)94.1%
Missing275
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean126.98661
Minimum126.55236
Maximum127.70215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2024-05-10T20:38:14.956964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55236
5-th percentile126.72613
Q1126.80928
median127.01156
Q3127.11597
95-th percentile127.24859
Maximum127.70215
Range1.1497961
Interquartile range (IQR)0.30669102

Descriptive statistics

Standard deviation0.18786353
Coefficient of variation (CV)0.0014793964
Kurtosis0.27453127
Mean126.98661
Median Absolute Deviation (MAD)0.13345153
Skewness0.36304469
Sum148193.37
Variance0.035292706
MonotonicityNot monotonic
2024-05-10T20:38:15.391330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9835493261 24
 
1.7%
126.8700052143 7
 
0.5%
127.1426886465 3
 
0.2%
127.1409110928 3
 
0.2%
126.7613834257 3
 
0.2%
126.7306929431 2
 
0.1%
126.7875971678 2
 
0.1%
126.776678513 2
 
0.1%
127.1387590868 2
 
0.1%
127.0308894167 2
 
0.1%
Other values (1088) 1117
77.5%
(Missing) 275
 
19.1%
ValueCountFrequency (%)
126.5523555323 1
0.1%
126.5966352318 1
0.1%
126.601604173 1
0.1%
126.607064602 1
0.1%
126.6184487325 1
0.1%
126.6236325537 1
0.1%
126.6238338609 1
0.1%
126.6246956053 1
0.1%
126.6248942624 1
0.1%
126.6250481619 1
0.1%
ValueCountFrequency (%)
127.702151627 1
0.1%
127.6969744807 1
0.1%
127.6737835358 1
0.1%
127.6379372926 1
0.1%
127.6367921491 1
0.1%
127.6320361005 1
0.1%
127.6252918393 1
0.1%
127.61594849 1
0.1%
127.575934941 1
0.1%
127.5150104334 1
0.1%

Interactions

2024-05-10T20:38:04.240056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:02.782790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:03.468618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:04.466581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:02.996275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:03.739455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:04.699517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:03.219321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:03.966146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:38:15.617860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명우편번호WGS84위도WGS84경도
시군명1.0000.9900.9760.948
우편번호0.9901.0000.9290.859
WGS84위도0.9760.9291.0000.684
WGS84경도0.9480.8590.6841.000
2024-05-10T20:38:15.842793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호WGS84위도WGS84경도시군명
우편번호1.000-0.9120.2580.914
WGS84위도-0.9121.000-0.2740.835
WGS84경도0.258-0.2741.0000.722
시군명0.9140.8350.7221.000

Missing values

2024-05-10T20:38:05.029352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:38:05.487056image/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.
2024-05-10T20:38:06.007989image/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

시군명업체명도로명주소지번주소우편번호전화번호WGS84위도WGS84경도
0가평군가평동물병원<NA>경기도 가평군 가평읍 읍내리 457번지 5호12413031-582-7582<NA><NA>
1가평군가평축산농협 동물병원<NA>경기도 가평군 가평읍 대곡리<NA>031-582-4111<NA><NA>
2가평군경기 동물병원경기도 가평군 청평면 청평중앙로 8경기도 가평군 청평면 청평리 438-23번지 경기동물병원12453031-584-128237.73585127.415936
3가평군선진가축병원(산업동물출장진료전문병원)경기도 가평군 가평읍 향교로 4경기도 가평군 가평읍 읍내리 535번지 2호12417070-8739-638837.829653127.510295
4가평군설악동물병원<NA>경기도 가평군 설악면 신천리 454번지 3호12467031-584-3063<NA><NA>
5가평군우랑동물병원경기도 가평군 가평읍 가화로 55-12경기도 가평군 가평읍 대곡리 166-1번지 대곡리 166번지 1호12420031-582-411137.82493127.51501
6가평군청평동물병원경기도 가평군 청평면 청평중앙로 55-1경기도 가평군 청평면 청평리 465-25번지 이화장12452031-585-758337.73844127.42045
7가평군현리 동물병원<NA>경기도 가평군 조종면 현리 303번지 6호12437031-585-0096<NA><NA>
8고양시(사)동물구조단체생명공감경기도 고양시 일산서구 가좌1로 8경기도 고양시 일산서구 가좌동 1087번지 가좌마을5단지 305호10211031-919-450437.690852126.721996
9고양시(주)우연컴퍼니경기도 고양시 일산동구 호수로 646-24경기도 고양시 일산동구 장항동 756-2번지 208-A23호10401***********37.659707126.767829
시군명업체명도로명주소지번주소우편번호전화번호WGS84위도WGS84경도
1432화성시퍼피움경기도 화성시 동탄기흥로520번나길 16경기도 화성시 영천동 804번지 4호 1층18470***********37.20616127.093973
1433화성시페이블주식회사경기도 화성시 동탄대로 635경기도 화성시 영천동 853-3번지 SH TIME SQUARE I 719호18468***********37.20996127.0981
1434화성시한빛동물병원경기도 화성시 남양읍 남양성지로 67경기도 화성시 남양읍 남양리 509번지18261031-356-431137.20698126.811083
1435화성시해나동물병원<NA>경기도 화성시 목동 496번지 2호<NA>031-378-7599<NA><NA>
1436화성시해솔동물병원경기도 화성시 동탄원천로 354-11경기도 화성시 능동 1065-2번지 106~107호18423031-8003-759537.218786127.057916
1437화성시향남메디동물병원경기도 화성시 향남읍 발안로 107경기도 화성시 향남읍 행정리 474번지 6호 태성플라자 101호18591031-359-827537.131722126.922378
1438화성시현대동물병원경기도 화성시 남양읍 남양시장로 38-4경기도 화성시 남양읍 남양리 563번지 무지개아파트 103호18261031-357-911937.208552126.81321
1439화성시호야펫 화성점<NA>경기도 화성시 진안동 859번지 4호18392***********<NA><NA>
1440화성시홍익메디칼동물병원<NA>경기도 화성시 우정읍 조암리 230번지 9호18566031-358-0200<NA><NA>
1441화성시힐링동물의료센터<NA>경기도 화성시 반월동 27번지 5호18379031-202-7512<NA><NA>

Duplicate rows

Most frequently occurring

시군명업체명도로명주소지번주소우편번호전화번호WGS84위도WGS84경도# duplicates
5양주시(사단)한국동물구조관리협회경기도 양주시 남면 감악산로 63-37경기도 양주시 남면 상수리 410-1번지11409031-867-911937.870117126.9835497
6양주시한국동물구조관리협회경기도 양주시 남면 감악산로 63-37경기도 양주시 남면 상수리 410-1번지11409031-867-911937.870117126.9835497
2안산시(사)한국야생동물보호협회경기도 안산시 상록구 청곡길 50경기도 안산시 상록구 부곡동 231-5번지15301031-296-012437.340254126.8700053
4양주시(사)한국동물구조관리협회경기도 양주시 남면 감악산로 63-37경기도 양주시 남면 상수리 410-1번지11409031-867-911937.870117126.9835493
0광주시모란동물병원<NA>경기도 광주시 경안동 96번지 6호12755031-767-7588<NA><NA>2
1광주시서울동물메디컬센터경기도 광주시 신현로 89경기도 광주시 신현동 674번지12821031-8022-758237.360416127.1567312
3안산시(사)한국야생동물보호협회경기도 안산시 상록구 청곡길 50경기도 안산시 상록구 부곡동 231-5번지 (사)한국야생동물보호협회15301031-296-012437.340254126.8700052
7양주시한국동물구조관리협회경기도 양주시 남면 감악산로 63-37경기도 양주시 남면 상수리 410-1번지 한국동물구조관리협회11409031-867-911937.870117126.9835492