Overview

Dataset statistics

Number of variables10
Number of observations4746
Missing cells2571
Missing cells (%)5.4%
Duplicate rows116
Duplicate rows (%)2.4%
Total size in memory389.4 KiB
Average record size in memory84.0 B

Variable types

Categorical2
Text4
Numeric4

Dataset

Description산재보험 지정 약국 현황
Author근로복지공단
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=KI8DUWAM91OT5DHX3STA28494814&infSeq=1

Alerts

Dataset has 116 (2.4%) duplicate rowsDuplicates
시군명 is highly overall correlated with 우편번호 and 3 other fieldsHigh correlation
관할지사 is highly overall correlated with 우편번호 and 3 other fieldsHigh correlation
우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
도로명주소 has 282 (5.9%) missing valuesMissing
우편번호 has 114 (2.4%) missing valuesMissing
전화번호 has 66 (1.4%) missing valuesMissing
팩스번호 has 1723 (36.3%) missing valuesMissing
WGS84위도 has 193 (4.1%) missing valuesMissing
WGS84경도 has 193 (4.1%) missing valuesMissing
팩스번호 is highly skewed (γ1 = 54.97909096)Skewed

Reproduction

Analysis started2023-12-10 21:29:49.669023
Analysis finished2023-12-10 21:29:52.800156
Duration3.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
부천시
462 
성남시
450 
수원시
395 
고양시
339 
안산시
322 
Other values (26)
2778 

Length

Max length4
Median length3
Mean length3.1038769
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 462
 
9.7%
성남시 450
 
9.5%
수원시 395
 
8.3%
고양시 339
 
7.1%
안산시 322
 
6.8%
안양시 278
 
5.9%
의정부시 232
 
4.9%
남양주시 217
 
4.6%
용인시 202
 
4.3%
평택시 173
 
3.6%
Other values (21) 1676
35.3%

Length

2023-12-11T06:29:52.874644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 462
 
9.7%
성남시 450
 
9.5%
수원시 395
 
8.3%
고양시 339
 
7.1%
안산시 322
 
6.8%
안양시 278
 
5.9%
의정부시 232
 
4.9%
남양주시 217
 
4.6%
용인시 202
 
4.3%
평택시 173
 
3.6%
Other values (21) 1676
35.3%

기관명
Text

Distinct2508
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2023-12-11T06:29:53.142426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.1312684
Min length3

Characters and Unicode

Total characters24353
Distinct characters467
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1697 ?
Unique (%)35.8%

Sample

1st row가평온누리약국
2nd row가평중앙약국
3rd row가평참빛약국
4th row감초온누리약국
5th row고향약국
ValueCountFrequency (%)
약국 53
 
1.1%
중앙약국 34
 
0.7%
미소약국 28
 
0.6%
우리약국 27
 
0.6%
하나약국 25
 
0.5%
조은약국 24
 
0.5%
우리들약국 22
 
0.5%
대학약국 22
 
0.5%
소망약국 21
 
0.4%
푸른약국 20
 
0.4%
Other values (2503) 4565
94.3%
2023-12-11T06:29:53.555757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 4767
 
19.6%
국 4758
 
19.5%
리 593
 
2.4%
누 356
 
1.5%
온 356
 
1.5%
한 293
 
1.2%
성 255
 
1.0%
정 214
 
0.9%
메 211
 
0.9%
세 210
 
0.9%
Other values (457) 12340
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24008
98.6%
Decimal Number 166
 
0.7%
Space Separator 95
 
0.4%
Open Punctuation 27
 
0.1%
Close Punctuation 27
 
0.1%
Lowercase Letter 11
 
< 0.1%
Other Punctuation 8
 
< 0.1%
Dash Punctuation 6
 
< 0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 4767
 
19.9%
국 4758
 
19.8%
리 593
 
2.5%
누 356
 
1.5%
온 356
 
1.5%
한 293
 
1.2%
성 255
 
1.1%
정 214
 
0.9%
메 211
 
0.9%
세 210
 
0.9%
Other values (431) 11995
50.0%
Decimal Number
ValueCountFrequency (%)
1 38
22.9%
2 32
19.3%
5 30
18.1%
3 28
16.9%
6 24
14.5%
0 12
 
7.2%
7 1
 
0.6%
4 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
54.5%
t 1
 
9.1%
w 1
 
9.1%
s 1
 
9.1%
o 1
 
9.1%
r 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
20.0%
S 1
20.0%
F 1
20.0%
M 1
20.0%
I 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 3
37.5%
& 1
 
12.5%
Space Separator
ValueCountFrequency (%)
95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24008
98.6%
Common 329
 
1.4%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 4767
 
19.9%
국 4758
 
19.8%
리 593
 
2.5%
누 356
 
1.5%
온 356
 
1.5%
한 293
 
1.2%
성 255
 
1.1%
정 214
 
0.9%
메 211
 
0.9%
세 210
 
0.9%
Other values (431) 11995
50.0%
Common
ValueCountFrequency (%)
95
28.9%
1 38
 
11.6%
2 32
 
9.7%
5 30
 
9.1%
3 28
 
8.5%
( 27
 
8.2%
) 27
 
8.2%
6 24
 
7.3%
0 12
 
3.6%
- 6
 
1.8%
Other values (5) 10
 
3.0%
Latin
ValueCountFrequency (%)
e 6
37.5%
G 1
 
6.2%
S 1
 
6.2%
F 1
 
6.2%
t 1
 
6.2%
w 1
 
6.2%
M 1
 
6.2%
s 1
 
6.2%
o 1
 
6.2%
r 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24008
98.6%
ASCII 345
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 4767
 
19.9%
국 4758
 
19.8%
리 593
 
2.5%
누 356
 
1.5%
온 356
 
1.5%
한 293
 
1.2%
성 255
 
1.1%
정 214
 
0.9%
메 211
 
0.9%
세 210
 
0.9%
Other values (431) 11995
50.0%
ASCII
ValueCountFrequency (%)
95
27.5%
1 38
 
11.0%
2 32
 
9.3%
5 30
 
8.7%
3 28
 
8.1%
( 27
 
7.8%
) 27
 
7.8%
6 24
 
7.0%
0 12
 
3.5%
e 6
 
1.7%
Other values (16) 26
 
7.5%

관할지사
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
성남지사
659 
안양지사
609 
부천지사
597 
안산지사
491 
고양지사
477 
Other values (7)
1913 

Length

Max length5
Median length4
Mean length4.1576064
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남지사 659
13.9%
안양지사 609
12.8%
부천지사 597
12.6%
안산지사 491
10.3%
고양지사 477
10.1%
의정부지사 411
8.7%
수원지사 399
8.4%
남양주지사 337
7.1%
평택지사 303
6.4%
용인지사 301
6.3%
Other values (2) 162
 
3.4%

Length

2023-12-11T06:29:53.664765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남지사 659
13.9%
안양지사 609
12.8%
부천지사 597
12.6%
안산지사 491
10.3%
고양지사 477
10.1%
의정부지사 411
8.7%
수원지사 399
8.4%
남양주지사 337
7.1%
평택지사 303
6.4%
용인지사 301
6.3%
Other values (2) 162
 
3.4%

도로명주소
Text

MISSING 

Distinct3111
Distinct (%)69.7%
Missing282
Missing (%)5.9%
Memory size37.2 KiB
2023-12-11T06:29:53.937182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length18.354839
Min length13

Characters and Unicode

Total characters81936
Distinct characters305
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

Unique2282 ?
Unique (%)51.1%

Sample

1st row경기도 가평군 가평읍 가화로 113
2nd row경기도 가평군 가평읍 연인1길 1
3rd row경기도 가평군 가평읍 가화로 55-12
4th row경기도 가평군 설악면 신천중앙로88번길 1
5th row경기도 가평군 설악면 한서로 9
ValueCountFrequency (%)
경기도 4464
 
22.0%
부천시 441
 
2.2%
성남시 425
 
2.1%
수원시 382
 
1.9%
고양시 320
 
1.6%
안산시 313
 
1.5%
안양시 248
 
1.2%
의정부시 224
 
1.1%
남양주시 210
 
1.0%
용인시 186
 
0.9%
Other values (2404) 13074
64.4%
2023-12-11T06:29:54.371206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15823
19.3%
경 4682
 
5.7%
시 4670
 
5.7%
기 4579
 
5.6%
도 4570
 
5.6%
로 4309
 
5.3%
1 2847
 
3.5%
구 2066
 
2.5%
2 1926
 
2.4%
3 1659
 
2.0%
Other values (295) 34805
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51703
63.1%
Space Separator 15823
 
19.3%
Decimal Number 13911
 
17.0%
Dash Punctuation 497
 
0.6%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 4682
 
9.1%
시 4670
 
9.0%
기 4579
 
8.9%
도 4570
 
8.8%
로 4309
 
8.3%
구 2066
 
4.0%
양 1204
 
2.3%
안 1192
 
2.3%
길 1043
 
2.0%
남 939
 
1.8%
Other values (282) 22449
43.4%
Decimal Number
ValueCountFrequency (%)
1 2847
20.5%
2 1926
13.8%
3 1659
11.9%
4 1246
9.0%
5 1184
8.5%
7 1093
 
7.9%
6 1082
 
7.8%
8 1073
 
7.7%
0 950
 
6.8%
9 851
 
6.1%
Space Separator
ValueCountFrequency (%)
15823
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 497
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51703
63.1%
Common 30233
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 4682
 
9.1%
시 4670
 
9.0%
기 4579
 
8.9%
도 4570
 
8.8%
로 4309
 
8.3%
구 2066
 
4.0%
양 1204
 
2.3%
안 1192
 
2.3%
길 1043
 
2.0%
남 939
 
1.8%
Other values (282) 22449
43.4%
Common
ValueCountFrequency (%)
15823
52.3%
1 2847
 
9.4%
2 1926
 
6.4%
3 1659
 
5.5%
4 1246
 
4.1%
5 1184
 
3.9%
7 1093
 
3.6%
6 1082
 
3.6%
8 1073
 
3.5%
0 950
 
3.1%
Other values (3) 1350
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51703
63.1%
ASCII 30233
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15823
52.3%
1 2847
 
9.4%
2 1926
 
6.4%
3 1659
 
5.5%
4 1246
 
4.1%
5 1184
 
3.9%
7 1093
 
3.6%
6 1082
 
3.6%
8 1073
 
3.5%
0 950
 
3.1%
Other values (3) 1350
 
4.5%
Hangul
ValueCountFrequency (%)
경 4682
 
9.1%
시 4670
 
9.0%
기 4579
 
8.9%
도 4570
 
8.8%
로 4309
 
8.3%
구 2066
 
4.0%
양 1204
 
2.3%
안 1192
 
2.3%
길 1043
 
2.0%
남 939
 
1.8%
Other values (282) 22449
43.4%

지번주소
Text

Distinct4255
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2023-12-11T06:29:54.692017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length26.88917
Min length14

Characters and Unicode

Total characters127616
Distinct characters534
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

Unique3880 ?
Unique (%)81.8%

Sample

1st row경기도 가평군 가평읍 읍내리 468-22번지 가평온누리약국
2nd row경기도 가평군 가평읍 읍내리 476-7번지 임내과의원
3rd row경기도 가평군 가평읍 대곡리 166-1번지 (가평약국)
4th row경기도 가평군 설악면 신천리 120-3번지 온누리감초약국
5th row경기도 가평군 설악면 신천리 121-2번지
ValueCountFrequency (%)
경기도 4637
 
17.2%
1층 1026
 
3.8%
부천시 462
 
1.7%
성남시 450
 
1.7%
수원시 395
 
1.5%
고양시 339
 
1.3%
안산시 322
 
1.2%
안양시 278
 
1.0%
의정부시 232
 
0.9%
남양주시 217
 
0.8%
Other values (5791) 18577
69.0%
2023-12-11T06:29:55.143978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22202
 
17.4%
1 7034
 
5.5%
시 4916
 
3.9%
기 4866
 
3.8%
경 4813
 
3.8%
지 4747
 
3.7%
도 4739
 
3.7%
동 4738
 
3.7%
번 4477
 
3.5%
- 3669
 
2.9%
Other values (524) 61415
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74604
58.5%
Decimal Number 26275
 
20.6%
Space Separator 22202
 
17.4%
Dash Punctuation 3669
 
2.9%
Uppercase Letter 245
 
0.2%
Other Punctuation 227
 
0.2%
Close Punctuation 174
 
0.1%
Open Punctuation 174
 
0.1%
Lowercase Letter 22
 
< 0.1%
Math Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4916
 
6.6%
기 4866
 
6.5%
경 4813
 
6.5%
지 4747
 
6.4%
도 4739
 
6.4%
동 4738
 
6.4%
번 4477
 
6.0%
구 2171
 
2.9%
호 1752
 
2.3%
양 1427
 
1.9%
Other values (463) 35958
48.2%
Uppercase Letter
ValueCountFrequency (%)
B 36
14.7%
A 32
13.1%
C 24
 
9.8%
S 17
 
6.9%
T 16
 
6.5%
I 15
 
6.1%
H 14
 
5.7%
K 12
 
4.9%
M 10
 
4.1%
D 8
 
3.3%
Other values (13) 61
24.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
27.3%
l 3
13.6%
s 2
 
9.1%
t 2
 
9.1%
m 1
 
4.5%
a 1
 
4.5%
c 1
 
4.5%
k 1
 
4.5%
b 1
 
4.5%
n 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
1 7034
26.8%
2 2928
11.1%
0 2822
10.7%
3 2485
 
9.5%
4 2327
 
8.9%
5 2050
 
7.8%
6 1824
 
6.9%
7 1804
 
6.9%
8 1552
 
5.9%
9 1449
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 200
88.1%
/ 12
 
5.3%
. 10
 
4.4%
' 2
 
0.9%
: 1
 
0.4%
@ 1
 
0.4%
& 1
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
33.3%
Ⅱ 1
33.3%
Ⅲ 1
33.3%
Space Separator
ValueCountFrequency (%)
22202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3669
100.0%
Close Punctuation
ValueCountFrequency (%)
) 174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 174
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74604
58.5%
Common 52742
41.3%
Latin 270
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4916
 
6.6%
기 4866
 
6.5%
경 4813
 
6.5%
지 4747
 
6.4%
도 4739
 
6.4%
동 4738
 
6.4%
번 4477
 
6.0%
구 2171
 
2.9%
호 1752
 
2.3%
양 1427
 
1.9%
Other values (463) 35958
48.2%
Latin
ValueCountFrequency (%)
B 36
13.3%
A 32
 
11.9%
C 24
 
8.9%
S 17
 
6.3%
T 16
 
5.9%
I 15
 
5.6%
H 14
 
5.2%
K 12
 
4.4%
M 10
 
3.7%
D 8
 
3.0%
Other values (29) 86
31.9%
Common
ValueCountFrequency (%)
22202
42.1%
1 7034
 
13.3%
- 3669
 
7.0%
2 2928
 
5.6%
0 2822
 
5.4%
3 2485
 
4.7%
4 2327
 
4.4%
5 2050
 
3.9%
6 1824
 
3.5%
7 1804
 
3.4%
Other values (12) 3597
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74602
58.5%
ASCII 53009
41.5%
Number Forms 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22202
41.9%
1 7034
 
13.3%
- 3669
 
6.9%
2 2928
 
5.5%
0 2822
 
5.3%
3 2485
 
4.7%
4 2327
 
4.4%
5 2050
 
3.9%
6 1824
 
3.4%
7 1804
 
3.4%
Other values (48) 3864
 
7.3%
Hangul
ValueCountFrequency (%)
시 4916
 
6.6%
기 4866
 
6.5%
경 4813
 
6.5%
지 4747
 
6.4%
도 4739
 
6.4%
동 4738
 
6.4%
번 4477
 
6.0%
구 2171
 
2.9%
호 1752
 
2.3%
양 1427
 
1.9%
Other values (462) 35956
48.2%
Compat Jamo
ValueCountFrequency (%)
ㅁ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
33.3%
Ⅱ 1
33.3%
Ⅲ 1
33.3%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1581
Distinct (%)34.1%
Missing114
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean14082.245
Minimum10011
Maximum18616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.8 KiB
2023-12-11T06:29:55.284561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10355
Q112048
median14218.5
Q315865
95-th percentile17924.3
Maximum18616
Range8605
Interquartile range (IQR)3817

Descriptive statistics

Standard deviation2333.1568
Coefficient of variation (CV)0.16568074
Kurtosis-0.97684873
Mean14082.245
Median Absolute Deviation (MAD)2013.5
Skewness0.030477488
Sum65228961
Variance5443620.7
MonotonicityNot monotonic
2023-12-11T06:29:55.439417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15865 26
 
0.5%
13497 23
 
0.5%
13590 21
 
0.4%
10823 20
 
0.4%
11923 20
 
0.4%
12759 19
 
0.4%
15495 18
 
0.4%
14585 17
 
0.4%
17936 17
 
0.4%
12968 17
 
0.4%
Other values (1571) 4434
93.4%
(Missing) 114
 
2.4%
ValueCountFrequency (%)
10011 7
0.1%
10016 1
 
< 0.1%
10018 6
0.1%
10019 1
 
< 0.1%
10031 1
 
< 0.1%
10035 4
0.1%
10039 2
 
< 0.1%
10040 3
 
0.1%
10059 9
0.2%
10062 1
 
< 0.1%
ValueCountFrequency (%)
18616 1
 
< 0.1%
18611 6
0.1%
18606 1
 
< 0.1%
18603 1
 
< 0.1%
18600 2
 
< 0.1%
18598 1
 
< 0.1%
18593 7
0.1%
18592 6
0.1%
18591 1
 
< 0.1%
18567 3
0.1%

전화번호
Text

MISSING 

Distinct3653
Distinct (%)78.1%
Missing66
Missing (%)1.4%
Memory size37.2 KiB
2023-12-11T06:29:55.647250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length9.9792735
Min length1

Characters and Unicode

Total characters46703
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

Unique2916 ?
Unique (%)62.3%

Sample

1st row0315818777
2nd row0315827639
3rd row0315826904
4th row0315851008
5th row0315841902
ValueCountFrequency (%)
031 14
 
0.3%
0311111111 8
 
0.2%
0310000000 7
 
0.1%
0317945888 7
 
0.1%
0326529155 6
 
0.1%
0226124100 6
 
0.1%
0319540852 6
 
0.1%
0313773763 6
 
0.1%
0312556416 5
 
0.1%
0315336127 5
 
0.1%
Other values (3643) 4610
98.5%
2023-12-11T06:29:55.964193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 7801
16.7%
0 7521
16.1%
1 7189
15.4%
2 4106
8.8%
7 3846
8.2%
5 3819
8.2%
6 3243
6.9%
8 3212
6.9%
4 3150
6.7%
9 2814
 
6.0%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46701
> 99.9%
Dash Punctuation 1
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 7801
16.7%
0 7521
16.1%
1 7189
15.4%
2 4106
8.8%
7 3846
8.2%
5 3819
8.2%
6 3243
6.9%
8 3212
6.9%
4 3150
6.7%
9 2814
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46703
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 7801
16.7%
0 7521
16.1%
1 7189
15.4%
2 4106
8.8%
7 3846
8.2%
5 3819
8.2%
6 3243
6.9%
8 3212
6.9%
4 3150
6.7%
9 2814
 
6.0%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46703
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 7801
16.7%
0 7521
16.1%
1 7189
15.4%
2 4106
8.8%
7 3846
8.2%
5 3819
8.2%
6 3243
6.9%
8 3212
6.9%
4 3150
6.7%
9 2814
 
6.0%
Other values (2) 2
 
< 0.1%

팩스번호
Real number (ℝ)

MISSING  SKEWED 

Distinct1348
Distinct (%)44.6%
Missing1723
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean1.099974 × 1010
Minimum0
Maximum3.1111111 × 1013
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size41.8 KiB
2023-12-11T06:29:56.096359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31
Q131
median32
Q33.171934 × 108
95-th percentile5.0403019 × 109
Maximum3.1111111 × 1013
Range3.1111111 × 1013
Interquartile range (IQR)3.1719337 × 108

Descriptive statistics

Standard deviation5.6584011 × 1011
Coefficient of variation (CV)51.441227
Kurtosis3022.8001
Mean1.099974 × 1010
Median Absolute Deviation (MAD)30
Skewness54.979091
Sum3.3252213 × 1013
Variance3.2017503 × 1023
MonotonicityNot monotonic
2023-12-11T06:29:56.221329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 1334
28.1%
32 160
 
3.4%
2 58
 
1.2%
310000000 7
 
0.1%
317545006 4
 
0.1%
323287401 4
 
0.1%
319540856 3
 
0.1%
226124101 3
 
0.1%
317810305 3
 
0.1%
314290201 3
 
0.1%
Other values (1338) 1444
30.4%
(Missing) 1723
36.3%
ValueCountFrequency (%)
0 2
 
< 0.1%
2 58
 
1.2%
31 1334
28.1%
32 160
 
3.4%
33 1
 
< 0.1%
53 1
 
< 0.1%
70 3
 
0.1%
5024 1
 
< 0.1%
315854 1
 
< 0.1%
23711370 1
 
< 0.1%
ValueCountFrequency (%)
31111111111111 1
< 0.1%
50242903375 1
< 0.1%
30334443823 1
< 0.1%
30334427531 1
< 0.1%
30334422468 1
< 0.1%
30334419066 1
< 0.1%
30334418997 1
< 0.1%
30334417541 1
< 0.1%
30334412191 1
< 0.1%
30331329862 1
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3181
Distinct (%)69.9%
Missing193
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean37.452173
Minimum36.960846
Maximum38.101733
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.8 KiB
2023-12-11T06:29:56.346634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.960846
5-th percentile37.115108
Q137.307911
median37.439818
Q337.611055
95-th percentile37.764896
Maximum38.101733
Range1.1408878
Interquartile range (IQR)0.30314311

Descriptive statistics

Standard deviation0.20429255
Coefficient of variation (CV)0.0054547582
Kurtosis-0.10789255
Mean37.452173
Median Absolute Deviation (MAD)0.14574704
Skewness0.13117186
Sum170519.74
Variance0.041735445
MonotonicityNot monotonic
2023-12-11T06:29:56.491978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3929799932 10
 
0.2%
37.3188431542 8
 
0.2%
37.1492375621 8
 
0.2%
37.8920935484 8
 
0.2%
37.6448480857 8
 
0.2%
37.5383224029 7
 
0.1%
37.856390783 7
 
0.1%
37.4088196883 7
 
0.1%
37.3873174337 6
 
0.1%
37.2696395308 6
 
0.1%
Other values (3171) 4478
94.4%
(Missing) 193
 
4.1%
ValueCountFrequency (%)
36.9608455198 1
< 0.1%
36.9617383356 1
< 0.1%
36.9644052069 1
< 0.1%
36.9787555958 1
< 0.1%
36.9790863294 1
< 0.1%
36.9828186461 1
< 0.1%
36.9837904271 1
< 0.1%
36.9841657112 1
< 0.1%
36.9847844212 1
< 0.1%
36.9848259449 1
< 0.1%
ValueCountFrequency (%)
38.1017333347 1
 
< 0.1%
38.1004724105 1
 
< 0.1%
38.0993630893 1
 
< 0.1%
38.0908758389 1
 
< 0.1%
38.0903804694 3
0.1%
38.0900775662 1
 
< 0.1%
38.0899913009 1
 
< 0.1%
38.0360433173 1
 
< 0.1%
38.0274953547 1
 
< 0.1%
38.0270812781 2
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3181
Distinct (%)69.9%
Missing193
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean126.99234
Minimum126.58256
Maximum127.63987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.8 KiB
2023-12-11T06:29:56.647424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58256
5-th percentile126.75015
Q1126.82184
median126.99428
Q3127.12864
95-th percentile127.28388
Maximum127.63987
Range1.0573133
Interquartile range (IQR)0.30679437

Descriptive statistics

Standard deviation0.18813181
Coefficient of variation (CV)0.0014814421
Kurtosis0.26935474
Mean126.99234
Median Absolute Deviation (MAD)0.14776972
Skewness0.55478171
Sum578196.14
Variance0.035393576
MonotonicityNot monotonic
2023-12-11T06:29:56.771626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.962257956 10
 
0.2%
126.834869809 8
 
0.2%
127.0638392059 8
 
0.2%
127.0526012919 8
 
0.2%
126.7920849948 8
 
0.2%
127.2043069537 7
 
0.1%
126.783973727 7
 
0.1%
127.2584226123 7
 
0.1%
127.1224705884 6
 
0.1%
127.1512899398 6
 
0.1%
Other values (3171) 4478
94.4%
(Missing) 193
 
4.1%
ValueCountFrequency (%)
126.5825555862 3
0.1%
126.5833826942 1
 
< 0.1%
126.5852196596 1
 
< 0.1%
126.5877251202 1
 
< 0.1%
126.5981167495 1
 
< 0.1%
126.5984311406 1
 
< 0.1%
126.5987730066 1
 
< 0.1%
126.5991171577 1
 
< 0.1%
126.5999278147 1
 
< 0.1%
126.6001738151 1
 
< 0.1%
ValueCountFrequency (%)
127.6398688676 1
 
< 0.1%
127.6386455655 1
 
< 0.1%
127.6372797797 1
 
< 0.1%
127.6369058095 1
 
< 0.1%
127.6367585457 1
 
< 0.1%
127.6361798272 1
 
< 0.1%
127.6355890297 1
 
< 0.1%
127.6354191999 2
< 0.1%
127.6340960896 3
0.1%
127.6332866478 1
 
< 0.1%

Interactions

2023-12-11T06:29:52.082843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:50.803094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.132225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.499395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:52.168091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:50.881281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.218145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.577189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:52.258234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:50.969661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.308780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.703138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:52.343220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.050541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.407665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:51.795185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:29:56.870112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명관할지사우편번호팩스번호WGS84위도WGS84경도
시군명1.0001.0000.9920.0480.9750.957
관할지사1.0001.0000.9480.0000.8610.824
우편번호0.9920.9481.0000.0350.9240.879
팩스번호0.0480.0000.0351.0000.1140.000
WGS84위도0.9750.8610.9240.1141.0000.718
WGS84경도0.9570.8240.8790.0000.7181.000
2023-12-11T06:29:56.968451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명관할지사
시군명1.0000.995
관할지사0.9951.000
2023-12-11T06:29:57.042626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호팩스번호WGS84위도WGS84경도시군명관할지사
우편번호1.000-0.103-0.9030.0700.9330.801
팩스번호-0.1031.0000.134-0.0420.0410.000
WGS84위도-0.9030.1341.000-0.1560.8340.595
WGS84경도0.070-0.042-0.1561.0000.7600.534
시군명0.9330.0410.8340.7601.0000.995
관할지사0.8010.0000.5950.5340.9951.000

Missing values

2023-12-11T06:29:52.463715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:29:52.596971image/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.
2023-12-11T06:29:52.724463image/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

시군명기관명관할지사도로명주소지번주소우편번호전화번호팩스번호WGS84위도WGS84경도
0가평군가평온누리약국춘천지사경기도 가평군 가평읍 가화로 113경기도 가평군 가평읍 읍내리 468-22번지 가평온누리약국124180315818777<NA>37.829734127.513364
1가평군가평중앙약국춘천지사경기도 가평군 가평읍 연인1길 1경기도 가평군 가평읍 읍내리 476-7번지 임내과의원12418031582763931582854937.829355127.513682
2가평군가평참빛약국춘천지사경기도 가평군 가평읍 가화로 55-12경기도 가평군 가평읍 대곡리 166-1번지 (가평약국)12420031582690431582690437.82493127.51501
3가평군감초온누리약국춘천지사경기도 가평군 설악면 신천중앙로88번길 1경기도 가평군 설악면 신천리 120-3번지 온누리감초약국124650315851008<NA>37.676905127.493752
4가평군고향약국춘천지사경기도 가평군 설악면 한서로 9경기도 가평군 설악면 신천리 121-2번지124650315841902<NA>37.676716127.494976
5가평군굿모닝약국춘천지사경기도 가평군 청평면 청평중앙로 45-1경기도 가평군 청평면 청평리 465-11번지1245203158546383137.737926127.419577
6가평군대신약국춘천지사경기도 가평군 가평읍 정간내로 1경기도 가평군 가평읍 읍내리 445번지 대신약국124120315816738<NA>37.831654127.513023
7가평군보령약국(최성규)춘천지사경기도 가평군 가평읍 가화로 123경기도 가평군 가평읍 읍내리 470-3번지 보령약국124180315827639<NA>37.830608127.513205
8가평군약손약국춘천지사경기도 가평군 가평읍 가화로 54경기도 가평군 가평읍 대곡리 167-2번지124190315289327<NA>37.824731127.515817
9가평군약손약국춘천지사경기도 가평군 가평읍 정간내로 1경기도 가평군 가평읍 읍내리 445번지 약손약국124120315829327<NA>37.831654127.513023
시군명기관명관할지사도로명주소지번주소우편번호전화번호팩스번호WGS84위도WGS84경도
4736화성시화성약국화성지사경기도 화성시 향남읍 삼천병마로 189경기도 화성시 향남읍 평리 257-5번지 (1층, 화성약국)18593031353000131353677437.130046126.909646
4737화성시화성약국화성지사경기도 화성시 향남읍 삼천병마로 189경기도 화성시 향남읍 평리 257-5번지 화성약국18593031353000131353677437.130046126.909646
4738화성시화성제일약국화성지사경기도 화성시 남양읍 남양로930번길 4경기도 화성시 남양읍 북양리 256-8번지 1층1825507075762575<NA>37.218712126.832402
4739화성시화성프라자약국화성지사경기도 화성시 남양읍 남양성지로 147경기도 화성시 남양읍 남양리 1268번지 아이스플라자 104호18261031355870731355914137.209839126.819058
4740화성시화성프라자약국화성지사경기도 화성시 남양읍 남양성지로 147경기도 화성시 남양읍 남양리 1268번지 아이리스프라자 1층18261031355870731355870837.209839126.819058
4741화성시화인약국화성지사경기도 화성시 병점1로 221경기도 화성시 진안동 876-4번지 화인메디컬프라자184040318986931<NA>37.213605127.041818
4742화성시화인약국화성지사경기도 화성시 병점1로 221경기도 화성시 진안동 876-4번지 화인메디칼 106호184040318986931<NA>37.213605127.041818
4743화성시회춘당약국수원지사경기도 화성시 향남읍 평3길 19경기도 화성시 향남읍 평리 118-10185930313530039<NA>37.131409126.90824
4744화성시희망약국화성지사<NA>경기 화성시 병점중앙로170번길 1 (진안동)<NA>031225839731<NA><NA>
4745화성시희망약국화성지사<NA>경기 화성시 병점중앙로170번길 1 (진안동)<NA>031225839731<NA><NA>

Duplicate rows

Most frequently occurring

시군명기관명관할지사도로명주소지번주소우편번호전화번호팩스번호WGS84위도WGS84경도# duplicates
96파주시21세기성심약국고양지사경기도 파주시 금정4길 29경기도 파주시 금촌동 775-6번지1092303194182753137.757101126.7777574
15남양주시세민약국남양주지사경기도 남양주시 퇴계원읍 퇴계원로 51경기도 남양주시 퇴계원읍 퇴계원리 281-1번지1212003157167343137.651449127.1418153
25부천시부천보룡약국부천지사경기도 부천시 계남로242번길 35-4경기도 부천시 중동 1066번지 1층145340323214536<NA>37.50501126.776473
44수원시그린팜중앙약국수원지사경기도 수원시 장안구 경수대로 1077경기도 수원시 장안구 파장동 576-1번지1634803125134113137.309068126.9942843
47수원시삼성약국수원지사경기도 수원시 팔달구 경수대로479번길 10-11경기도 수원시 팔달구 인계동 965-4번지1648103123832873137.269739127.0267143
79오산시뉴훼미리약국평택지사경기도 오산시 성호대로 24경기도 오산시 오산동 614-2번지1813003137737633137.149238127.0638393
82용인시신갈현대약국용인지사경기도 용인시 기흥구 신갈로 45경기도 용인시 기흥구 신갈동 71-12번지1706403128133883137.270722127.1054473
93의정부시햇살온누리약국의정부지사경기도 의정부시 상금로 33경기도 의정부시 금오동 80-19번지 이롬프라자 107호117640318462199<NA>37.757798127.0744253
100파주시법원약국고양지사경기도 파주시 법원읍 술이홀로 873경기도 파주시 법원읍 대능리 94-72번지1082603195828463137.849272126.8726333
108평택시효명약국평택지사<NA>경기 평택시 송탄로 31 (장당동)17784031667148831<NA><NA>3