Overview

Dataset statistics

Number of variables13
Number of observations587
Missing cells697
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.6 KiB
Average record size in memory109.2 B

Variable types

Categorical4
Text3
Numeric5
Boolean1

Dataset

Description공중이용시설 현황(업무시설)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=P64U9OK31D50Z2024AU71717772&infSeq=1

Alerts

다중이용업소여부 has constant value ""Constant
영업상태명 is highly overall correlated with 폐업일자 and 2 other fieldsHigh correlation
위생업태명 is highly overall correlated with 인허가일자 and 7 other fieldsHigh correlation
위생업종명 is highly overall correlated with 인허가일자 and 7 other fieldsHigh correlation
시군명 is highly overall correlated with 폐업일자 and 5 other fieldsHigh correlation
인허가일자 is highly overall correlated with 위생업종명 and 1 other fieldsHigh correlation
폐업일자 is highly overall correlated with 시군명 and 3 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84경도 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
영업상태명 is highly imbalanced (70.2%)Imbalance
위생업종명 is highly imbalanced (54.0%)Imbalance
위생업태명 is highly imbalanced (54.0%)Imbalance
폐업일자 has 556 (94.7%) missing valuesMissing
다중이용업소여부 has 57 (9.7%) missing valuesMissing
소재지도로명주소 has 35 (6.0%) missing valuesMissing
WGS84위도 has 24 (4.1%) missing valuesMissing
WGS84경도 has 24 (4.1%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -23.89729871)Skewed

Reproduction

Analysis started2023-12-10 22:56:28.337101
Analysis finished2023-12-10 22:56:32.019051
Duration3.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
성남시
85 
용인시
71 
수원시
71 
부천시
57 
안산시
44 
Other values (24)
259 

Length

Max length4
Median length3
Mean length3.0459966
Min length3

Unique

Unique6 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 85
14.5%
용인시 71
12.1%
수원시 71
12.1%
부천시 57
9.7%
안산시 44
 
7.5%
안양시 42
 
7.2%
광명시 32
 
5.5%
시흥시 25
 
4.3%
과천시 18
 
3.1%
구리시 17
 
2.9%
Other values (19) 125
21.3%

Length

2023-12-11T07:56:32.132611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 85
14.5%
용인시 71
12.1%
수원시 71
12.1%
부천시 57
9.7%
안산시 44
 
7.5%
안양시 42
 
7.2%
광명시 32
 
5.5%
시흥시 25
 
4.3%
과천시 18
 
3.1%
구리시 17
 
2.9%
Other values (19) 125
21.3%

사업장명
Text

Distinct528
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T07:56:32.379905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.0647359
Min length1

Characters and Unicode

Total characters4147
Distinct characters366
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique505 ?
Unique (%)86.0%

Sample

1st row가평군청
2nd row능곡교회
3rd row(주)국민은행
4th row남지빌딩
5th row서울방송탄현제작센터
ValueCountFrequency (%)
0 25
 
3.9%
없음 7
 
1.1%
건축물 7
 
1.1%
한국전력공사 6
 
0.9%
위브더스테이트 5
 
0.8%
명칭없음 4
 
0.6%
중소기업은행 3
 
0.5%
삼성생명 3
 
0.5%
주)국민은행 2
 
0.3%
조흥은행 2
 
0.3%
Other values (549) 578
90.0%
2023-12-11T07:56:32.778658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 100
 
2.4%
주 95
 
2.3%
) 89
 
2.1%
( 87
 
2.1%
사 81
 
2.0%
국 80
 
1.9%
청 79
 
1.9%
동 76
 
1.8%
원 67
 
1.6%
한 63
 
1.5%
Other values (356) 3330
80.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3727
89.9%
Decimal Number 102
 
2.5%
Close Punctuation 89
 
2.1%
Open Punctuation 87
 
2.1%
Uppercase Letter 67
 
1.6%
Space Separator 55
 
1.3%
Dash Punctuation 9
 
0.2%
Other Punctuation 6
 
0.1%
Lowercase Letter 3
 
0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 100
 
2.7%
주 95
 
2.5%
사 81
 
2.2%
국 80
 
2.1%
청 79
 
2.1%
동 76
 
2.0%
원 67
 
1.8%
한 63
 
1.7%
시 63
 
1.7%
소 63
 
1.7%
Other values (316) 2960
79.4%
Uppercase Letter
ValueCountFrequency (%)
T 11
16.4%
S 10
14.9%
K 8
11.9%
I 6
9.0%
N 4
 
6.0%
E 4
 
6.0%
O 4
 
6.0%
F 3
 
4.5%
H 3
 
4.5%
G 2
 
3.0%
Other values (9) 12
17.9%
Decimal Number
ValueCountFrequency (%)
0 36
35.3%
1 23
22.5%
2 11
 
10.8%
3 10
 
9.8%
6 7
 
6.9%
4 5
 
4.9%
7 3
 
2.9%
5 3
 
2.9%
8 3
 
2.9%
9 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
50.0%
, 1
 
16.7%
. 1
 
16.7%
& 1
 
16.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3727
89.9%
Common 348
 
8.4%
Latin 72
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 100
 
2.7%
주 95
 
2.5%
사 81
 
2.2%
국 80
 
2.1%
청 79
 
2.1%
동 76
 
2.0%
원 67
 
1.8%
한 63
 
1.7%
시 63
 
1.7%
소 63
 
1.7%
Other values (316) 2960
79.4%
Latin
ValueCountFrequency (%)
T 11
15.3%
S 10
13.9%
K 8
11.1%
I 6
 
8.3%
N 4
 
5.6%
E 4
 
5.6%
O 4
 
5.6%
F 3
 
4.2%
l 3
 
4.2%
H 3
 
4.2%
Other values (12) 16
22.2%
Common
ValueCountFrequency (%)
) 89
25.6%
( 87
25.0%
55
15.8%
0 36
10.3%
1 23
 
6.6%
2 11
 
3.2%
3 10
 
2.9%
- 9
 
2.6%
6 7
 
2.0%
4 5
 
1.4%
Other values (8) 16
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3727
89.9%
ASCII 418
 
10.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 100
 
2.7%
주 95
 
2.5%
사 81
 
2.2%
국 80
 
2.1%
청 79
 
2.1%
동 76
 
2.0%
원 67
 
1.8%
한 63
 
1.7%
시 63
 
1.7%
소 63
 
1.7%
Other values (316) 2960
79.4%
ASCII
ValueCountFrequency (%)
) 89
21.3%
( 87
20.8%
55
13.2%
0 36
8.6%
1 23
 
5.5%
2 11
 
2.6%
T 11
 
2.6%
S 10
 
2.4%
3 10
 
2.4%
- 9
 
2.2%
Other values (28) 77
18.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

인허가일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct272
Distinct (%)46.4%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean19990834
Minimum199402
Maximum20160126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T07:56:32.939426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199402
5-th percentile19910418
Q119960549
median20050729
Q320100302
95-th percentile20120703
Maximum20160126
Range19960724
Interquartile range (IQR)139753

Descriptive statistics

Standard deviation822494.94
Coefficient of variation (CV)0.041143603
Kurtosis575.97916
Mean19990834
Median Absolute Deviation (MAD)50387
Skewness-23.897299
Sum1.1714629 × 1010
Variance6.7649792 × 1011
MonotonicityNot monotonic
2023-12-11T07:56:33.088056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100517 38
 
6.5%
20070222 26
 
4.4%
20031001 23
 
3.9%
20101126 21
 
3.6%
20121206 19
 
3.2%
20100928 16
 
2.7%
20100302 14
 
2.4%
20101029 13
 
2.2%
20080102 12
 
2.0%
20050729 11
 
1.9%
Other values (262) 393
67.0%
ValueCountFrequency (%)
199402 1
0.2%
19731016 1
0.2%
19771213 1
0.2%
19791102 1
0.2%
19810623 1
0.2%
19810627 1
0.2%
19810929 1
0.2%
19811103 1
0.2%
19840726 1
0.2%
19850715 1
0.2%
ValueCountFrequency (%)
20160126 1
 
0.2%
20140325 2
 
0.3%
20130318 2
 
0.3%
20130226 1
 
0.2%
20121217 2
 
0.3%
20121206 19
3.2%
20120920 1
 
0.2%
20120904 2
 
0.3%
20120101 1
 
0.2%
20111007 2
 
0.3%

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
운영중
556 
폐업 등
 
31

Length

Max length4
Median length3
Mean length3.0528109
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 556
94.7%
폐업 등 31
 
5.3%

Length

2023-12-11T07:56:33.262738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:56:33.364034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 556
90.0%
폐업 31
 
5.0%
등 31
 
5.0%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)38.7%
Missing556
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean20090516
Minimum20070319
Maximum20141023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T07:56:33.441060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070319
5-th percentile20070319
Q120070319
median20070416
Q320110968
95-th percentile20135562
Maximum20141023
Range70704
Interquartile range (IQR)40648.5

Descriptive statistics

Standard deviation26478.357
Coefficient of variation (CV)0.0013179531
Kurtosis-1.0346912
Mean20090516
Median Absolute Deviation (MAD)97
Skewness0.80972025
Sum6.2280599 × 108
Variance7.0110339 × 108
MonotonicityNot monotonic
2023-12-11T07:56:33.545066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20070319 11
 
1.9%
20070416 7
 
1.2%
20101231 3
 
0.5%
20130416 2
 
0.3%
20141023 1
 
0.2%
20120704 1
 
0.2%
20130620 1
 
0.2%
20130806 1
 
0.2%
20140318 1
 
0.2%
20090410 1
 
0.2%
Other values (2) 2
 
0.3%
(Missing) 556
94.7%
ValueCountFrequency (%)
20070319 11
1.9%
20070416 7
1.2%
20090410 1
 
0.2%
20100331 1
 
0.2%
20101231 3
 
0.5%
20120704 1
 
0.2%
20120831 1
 
0.2%
20130416 2
 
0.3%
20130620 1
 
0.2%
20130806 1
 
0.2%
ValueCountFrequency (%)
20141023 1
 
0.2%
20140318 1
 
0.2%
20130806 1
 
0.2%
20130620 1
 
0.2%
20130416 2
0.3%
20120831 1
 
0.2%
20120704 1
 
0.2%
20101231 3
0.5%
20100331 1
 
0.2%
20090410 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing57
Missing (%)9.7%
Memory size1.3 KiB
False
530 
(Missing)
57 
ValueCountFrequency (%)
False 530
90.3%
(Missing) 57
 
9.7%
2023-12-11T07:56:33.649826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위생업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
공중이용시설
530 
<NA>
57 

Length

Max length6
Median length6
Mean length5.8057922
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공중이용시설 530
90.3%
<NA> 57
 
9.7%

Length

2023-12-11T07:56:33.752419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:56:33.852366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공중이용시설 530
90.3%
na 57
 
9.7%

위생업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
업무시설
530 
<NA>
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
업무시설 530
90.3%
<NA> 57
 
9.7%

Length

2023-12-11T07:56:33.958939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:56:34.045897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업무시설 530
90.3%
na 57
 
9.7%

소재지도로명주소
Text

MISSING 

Distinct540
Distinct (%)97.8%
Missing35
Missing (%)6.0%
Memory size4.7 KiB
2023-12-11T07:56:34.339622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length25.394928
Min length13

Characters and Unicode

Total characters14018
Distinct characters299
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)96.0%

Sample

1st row경기도 가평군 가평읍 석봉로 181
2nd row경기도 고양시 덕양구 토당로104번길 33-12 (토당동)
3rd row경기도 고양시 일산동구 강석로 149 (마두동,강촌프라자)
4th row경기도 고양시 덕양구 고양대로 1381 (성사동)
5th row경기도 고양시 일산서구 일현로 111 (탄현동,번지)
ValueCountFrequency (%)
경기도 552
 
17.9%
성남시 80
 
2.6%
수원시 62
 
2.0%
용인시 62
 
2.0%
분당구 58
 
1.9%
부천시 57
 
1.8%
안산시 43
 
1.4%
안양시 42
 
1.4%
기흥구 40
 
1.3%
동안구 34
 
1.1%
Other values (930) 2060
66.7%
2023-12-11T07:56:35.036349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2538
 
18.1%
기 609
 
4.3%
시 606
 
4.3%
경 584
 
4.2%
동 580
 
4.1%
도 563
 
4.0%
로 541
 
3.9%
) 518
 
3.7%
( 518
 
3.7%
1 391
 
2.8%
Other values (289) 6570
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8366
59.7%
Space Separator 2538
 
18.1%
Decimal Number 1895
 
13.5%
Close Punctuation 518
 
3.7%
Open Punctuation 518
 
3.7%
Other Punctuation 112
 
0.8%
Dash Punctuation 54
 
0.4%
Uppercase Letter 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 609
 
7.3%
시 606
 
7.2%
경 584
 
7.0%
동 580
 
6.9%
도 563
 
6.7%
로 541
 
6.5%
구 351
 
4.2%
안 189
 
2.3%
길 140
 
1.7%
원 134
 
1.6%
Other values (263) 4069
48.6%
Decimal Number
ValueCountFrequency (%)
1 391
20.6%
2 284
15.0%
3 213
11.2%
5 176
9.3%
0 154
 
8.1%
7 145
 
7.7%
4 144
 
7.6%
6 143
 
7.5%
8 135
 
7.1%
9 110
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
N 4
23.5%
I 4
23.5%
H 2
11.8%
T 2
11.8%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%
F 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 110
98.2%
. 1
 
0.9%
& 1
 
0.9%
Space Separator
ValueCountFrequency (%)
2538
100.0%
Close Punctuation
ValueCountFrequency (%)
) 518
100.0%
Open Punctuation
ValueCountFrequency (%)
( 518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8366
59.7%
Common 5635
40.2%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 609
 
7.3%
시 606
 
7.2%
경 584
 
7.0%
동 580
 
6.9%
도 563
 
6.7%
로 541
 
6.5%
구 351
 
4.2%
안 189
 
2.3%
길 140
 
1.7%
원 134
 
1.6%
Other values (263) 4069
48.6%
Common
ValueCountFrequency (%)
2538
45.0%
) 518
 
9.2%
( 518
 
9.2%
1 391
 
6.9%
2 284
 
5.0%
3 213
 
3.8%
5 176
 
3.1%
0 154
 
2.7%
7 145
 
2.6%
4 144
 
2.6%
Other values (7) 554
 
9.8%
Latin
ValueCountFrequency (%)
N 4
23.5%
I 4
23.5%
H 2
11.8%
T 2
11.8%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%
F 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8366
59.7%
ASCII 5652
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2538
44.9%
) 518
 
9.2%
( 518
 
9.2%
1 391
 
6.9%
2 284
 
5.0%
3 213
 
3.8%
5 176
 
3.1%
0 154
 
2.7%
7 145
 
2.6%
4 144
 
2.5%
Other values (16) 571
 
10.1%
Hangul
ValueCountFrequency (%)
기 609
 
7.3%
시 606
 
7.2%
경 584
 
7.0%
동 580
 
6.9%
도 563
 
6.7%
로 541
 
6.5%
구 351
 
4.2%
안 189
 
2.3%
길 140
 
1.7%
원 134
 
1.6%
Other values (263) 4069
48.6%

소재지지번주소
Text

Distinct575
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T07:56:35.322530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length22.07155
Min length15

Characters and Unicode

Total characters12956
Distinct characters249
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique565 ?
Unique (%)96.3%

Sample

1st row경기도 가평군 가평읍 읍내리 513번지
2nd row경기도 고양시 덕양구 토당동 56-3번지
3rd row경기도 고양시 일산동구 마두동 799-2번지 강촌프라자
4th row경기도 고양시 덕양구 성사동 703-8번지
5th row경기도 고양시 일산서구 탄현동 141번지 번지
ValueCountFrequency (%)
경기도 587
 
20.9%
성남시 85
 
3.0%
용인시 71
 
2.5%
수원시 71
 
2.5%
분당구 60
 
2.1%
부천시 57
 
2.0%
기흥구 46
 
1.6%
안산시 44
 
1.6%
안양시 42
 
1.5%
팔달구 40
 
1.4%
Other values (860) 1705
60.7%
2023-12-11T07:56:35.731643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2221
17.1%
기 636
 
4.9%
지 631
 
4.9%
시 618
 
4.8%
동 617
 
4.8%
도 596
 
4.6%
번 590
 
4.6%
경 589
 
4.5%
1 533
 
4.1%
- 396
 
3.1%
Other values (239) 5529
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7956
61.4%
Decimal Number 2318
 
17.9%
Space Separator 2221
 
17.1%
Dash Punctuation 396
 
3.1%
Other Punctuation 28
 
0.2%
Uppercase Letter 17
 
0.1%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 636
 
8.0%
지 631
 
7.9%
시 618
 
7.8%
동 617
 
7.8%
도 596
 
7.5%
번 590
 
7.4%
경 589
 
7.4%
구 362
 
4.6%
안 162
 
2.0%
원 129
 
1.6%
Other values (213) 3026
38.0%
Decimal Number
ValueCountFrequency (%)
1 533
23.0%
2 292
12.6%
3 250
10.8%
5 244
10.5%
4 202
 
8.7%
7 178
 
7.7%
6 177
 
7.6%
0 172
 
7.4%
8 160
 
6.9%
9 110
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
I 4
23.5%
N 4
23.5%
H 2
11.8%
T 2
11.8%
F 1
 
5.9%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 26
92.9%
. 1
 
3.6%
& 1
 
3.6%
Space Separator
ValueCountFrequency (%)
2221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 396
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7956
61.4%
Common 4983
38.5%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 636
 
8.0%
지 631
 
7.9%
시 618
 
7.8%
동 617
 
7.8%
도 596
 
7.5%
번 590
 
7.4%
경 589
 
7.4%
구 362
 
4.6%
안 162
 
2.0%
원 129
 
1.6%
Other values (213) 3026
38.0%
Common
ValueCountFrequency (%)
2221
44.6%
1 533
 
10.7%
- 396
 
7.9%
2 292
 
5.9%
3 250
 
5.0%
5 244
 
4.9%
4 202
 
4.1%
7 178
 
3.6%
6 177
 
3.6%
0 172
 
3.5%
Other values (7) 318
 
6.4%
Latin
ValueCountFrequency (%)
I 4
23.5%
N 4
23.5%
H 2
11.8%
T 2
11.8%
F 1
 
5.9%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7956
61.4%
ASCII 5000
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2221
44.4%
1 533
 
10.7%
- 396
 
7.9%
2 292
 
5.8%
3 250
 
5.0%
5 244
 
4.9%
4 202
 
4.0%
7 178
 
3.6%
6 177
 
3.5%
0 172
 
3.4%
Other values (16) 335
 
6.7%
Hangul
ValueCountFrequency (%)
기 636
 
8.0%
지 631
 
7.9%
시 618
 
7.8%
동 617
 
7.8%
도 596
 
7.5%
번 590
 
7.4%
경 589
 
7.4%
구 362
 
4.6%
안 162
 
2.0%
원 129
 
1.6%
Other values (213) 3026
38.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct325
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean402361.99
Minimum14409
Maximum487915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T07:56:35.857327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14409
5-th percentile14566
Q1425868
median440831
Q3460591.5
95-th percentile477501.3
Maximum487915
Range473506
Interquartile range (IQR)34723.5

Descriptive statistics

Standard deviation128471.65
Coefficient of variation (CV)0.31929369
Kurtosis5.1668341
Mean402361.99
Median Absolute Deviation (MAD)14982
Skewness-2.6343847
Sum2.3618649 × 108
Variance1.6504964 × 1010
MonotonicityNot monotonic
2023-12-11T07:56:36.004432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463824 17
 
2.9%
431815 13
 
2.2%
425801 12
 
2.0%
442835 9
 
1.5%
463825 8
 
1.4%
425868 8
 
1.4%
431811 8
 
1.4%
442834 7
 
1.2%
423836 7
 
1.2%
463870 7
 
1.2%
Other values (315) 491
83.6%
ValueCountFrequency (%)
14409 1
0.2%
14434 1
0.2%
14442 2
0.3%
14445 2
0.3%
14446 1
0.2%
14449 2
0.3%
14492 2
0.3%
14519 1
0.2%
14524 1
0.2%
14530 1
0.2%
ValueCountFrequency (%)
487915 1
 
0.2%
487805 1
 
0.2%
487803 1
 
0.2%
486803 1
 
0.2%
483100 1
 
0.2%
483030 3
0.5%
483020 4
0.7%
483010 1
 
0.2%
480849 1
 
0.2%
480848 2
0.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct549
Distinct (%)97.5%
Missing24
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean37.409946
Minimum36.990698
Maximum38.096517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T07:56:36.150831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990698
5-th percentile37.232241
Q137.307032
median37.387097
Q337.481429
95-th percentile37.735973
Maximum38.096517
Range1.1058185
Interquartile range (IQR)0.17439635

Descriptive statistics

Standard deviation0.15701798
Coefficient of variation (CV)0.0041972254
Kurtosis1.7721124
Mean37.409946
Median Absolute Deviation (MAD)0.08913953
Skewness0.89364139
Sum21061.8
Variance0.024654645
MonotonicityNot monotonic
2023-12-11T07:56:36.324888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4778909462 4
 
0.7%
37.2755271902 2
 
0.3%
37.4528395065 2
 
0.3%
37.4085616112 2
 
0.3%
37.2321387565 2
 
0.3%
37.2380398062 2
 
0.3%
37.3222450318 2
 
0.3%
37.2633631503 2
 
0.3%
37.2405152454 2
 
0.3%
37.3209928452 2
 
0.3%
Other values (539) 541
92.2%
(Missing) 24
 
4.1%
ValueCountFrequency (%)
36.990698213 1
0.2%
36.9915079652 1
0.2%
36.992297194 1
0.2%
37.0289362455 1
0.2%
37.0665995289 1
0.2%
37.0670332361 1
0.2%
37.0673353224 1
0.2%
37.0674693488 1
0.2%
37.068091733 1
0.2%
37.0808173906 1
0.2%
ValueCountFrequency (%)
38.0965166652 1
0.2%
37.942490453 1
0.2%
37.9232943209 1
0.2%
37.9046812612 1
0.2%
37.9036051104 1
0.2%
37.8966147652 1
0.2%
37.8946984341 1
0.2%
37.8927661327 1
0.2%
37.8922638664 1
0.2%
37.8922134798 1
0.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct549
Distinct (%)97.5%
Missing24
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean126.97943
Minimum126.54445
Maximum127.63663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-11T07:56:36.463782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54445
5-th percentile126.75187
Q1126.84188
median126.99811
Q3127.10984
95-th percentile127.17052
Maximum127.63663
Range1.0921824
Interquartile range (IQR)0.267966

Descriptive statistics

Standard deviation0.15542697
Coefficient of variation (CV)0.0012240327
Kurtosis0.088495793
Mean126.97943
Median Absolute Deviation (MAD)0.12246468
Skewness0.10033348
Sum71489.418
Variance0.024157543
MonotonicityNot monotonic
2023-12-11T07:56:36.612955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.864666872 4
 
0.7%
127.0525651077 2
 
0.3%
127.1584235005 2
 
0.3%
127.1423531109 2
 
0.3%
127.0835412501 2
 
0.3%
127.1118068919 2
 
0.3%
127.097401236 2
 
0.3%
127.1018651611 2
 
0.3%
127.1135191986 2
 
0.3%
126.8292640991 2
 
0.3%
Other values (539) 541
92.2%
(Missing) 24
 
4.1%
ValueCountFrequency (%)
126.5444458283 1
0.2%
126.5986993879 1
0.2%
126.6088191384 1
0.2%
126.6254496573 1
0.2%
126.6810691981 1
0.2%
126.68187307 1
0.2%
126.6969420067 1
0.2%
126.7085117709 1
0.2%
126.7121679694 1
0.2%
126.712630645 1
0.2%
ValueCountFrequency (%)
127.6366282067 1
0.2%
127.5094206698 1
0.2%
127.4871719211 1
0.2%
127.4473639758 1
0.2%
127.4414326284 1
0.2%
127.4144521463 1
0.2%
127.3273591789 1
0.2%
127.313486286 1
0.2%
127.3030107656 1
0.2%
127.2995138375 1
0.2%

Interactions

2023-12-11T07:56:30.868732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.156890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.593904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.003842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.438553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.973092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.253253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.675895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.094450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.543112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:31.065172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.354459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.772295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.208445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.623188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:31.173604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.436917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.864424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.280490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.697004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:31.278566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.516600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:29.934125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.364391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:30.773844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:56:36.732188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명폐업일자소재지우편번호WGS84위도WGS84경도
시군명1.000NaN0.5410.9290.9970.9850.961
인허가일자NaN1.000NaNNaNNaNNaNNaN
영업상태명0.541NaN1.000NaN0.1280.2520.355
폐업일자0.929NaNNaN1.0000.9890.9250.730
소재지우편번호0.997NaN0.1280.9891.0000.6600.811
WGS84위도0.985NaN0.2520.9250.6601.0000.769
WGS84경도0.961NaN0.3550.7300.8110.7691.000
2023-12-11T07:56:36.884066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명위생업태명위생업종명시군명
영업상태명1.0001.0001.0000.455
위생업태명1.0001.0001.0001.000
위생업종명1.0001.0001.0001.000
시군명0.4551.0001.0001.000
2023-12-11T07:56:37.016325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
인허가일자1.000-0.0300.193-0.1330.2430.0000.0001.0001.000
폐업일자-0.0301.000-0.0500.2450.1980.6321.0001.0001.000
소재지우편번호0.193-0.0501.000-0.1990.8990.9740.2111.0001.000
WGS84위도-0.1330.245-0.1991.000-0.2870.8760.1921.0001.000
WGS84경도0.2430.1980.899-0.2871.0000.7660.2701.0001.000
시군명0.0000.6320.9740.8760.7661.0000.4551.0001.000
영업상태명0.0001.0000.2110.1920.2700.4551.0001.0001.000
위생업종명1.0001.0001.0001.0001.0001.0001.0001.0001.000
위생업태명1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T07:56:31.466268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:56:31.717274image/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.
2023-12-11T07:56:31.896628image/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

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군가평군청19910716운영중<NA>N공중이용시설업무시설경기도 가평군 가평읍 석봉로 181경기도 가평군 가평읍 읍내리 513번지47780137.831122127.509421
1고양시능곡교회19961130운영중<NA>N공중이용시설업무시설경기도 고양시 덕양구 토당로104번길 33-12 (토당동)경기도 고양시 덕양구 토당동 56-3번지41281637.624823126.820163
2고양시(주)국민은행19961111운영중<NA>N공중이용시설업무시설경기도 고양시 일산동구 강석로 149 (마두동,강촌프라자)경기도 고양시 일산동구 마두동 799-2번지 강촌프라자41081137.653846126.777693
3고양시남지빌딩19970204운영중<NA>N공중이용시설업무시설경기도 고양시 덕양구 고양대로 1381 (성사동)경기도 고양시 덕양구 성사동 703-8번지41280737.654558126.8376
4고양시서울방송탄현제작센터19960615운영중<NA>N공중이용시설업무시설경기도 고양시 일산서구 일현로 111 (탄현동,번지)경기도 고양시 일산서구 탄현동 141번지 번지41184037.6968126.762576
5고양시한국주택은행일산지점19960820운영중<NA>N공중이용시설업무시설경기도 고양시 일산서구 중앙로 1414 (주엽동,번지)경기도 고양시 일산서구 주엽동 71-3번지 번지41184837.669647126.763241
6고양시고양시 일산구청19970203운영중<NA>N공중이용시설업무시설경기도 고양시 일산동구 중앙로 1256 (마두동)경기도 고양시 일산동구 마두동 815번지41081237.658868126.774957
7고양시증권예탁원19980525운영중<NA>N공중이용시설업무시설경기도 고양시 일산동구 호수로 358-8 (백석동)경기도 고양시 일산동구 백석동 1328번지41083537.638538126.786013
8고양시한일은행19960820운영중<NA>N공중이용시설업무시설경기도 고양시 일산동구 중앙로 1202 (마두동)경기도 고양시 일산동구 마두동 798번지41081137.654049126.777033
9고양시한국통신공사19961226운영중<NA>N공중이용시설업무시설경기도 고양시 덕양구 호국로790번길 59 (성사동)경기도 고양시 덕양구 성사동 398-1번지41280537.65547126.839372
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
577평택시국민은행송탄지점19930209운영중<NA>N공중이용시설업무시설경기도 평택시 탄현로 320 (지산동)경기도 평택시 지산동 763-3번지45911037.080817127.055872
578평택시엘지전자주식회사19930612운영중<NA>N공중이용시설업무시설경기도 평택시 진위면 엘지로 222경기도 평택시 진위면 청호리 19-1번지45186237.125364127.090623
579포천시포천시청19910413운영중<NA>N공중이용시설업무시설경기도 포천시 중앙로 87 (신읍동)경기도 포천시 신읍동 58-2번지48780337.894698127.200339
580포천시농업기술센터20060619운영중<NA>N공중이용시설업무시설경기도 포천시 신북면 틀못이길 11-88경기도 포천시 신북면 기지리 647-1번지48791537.923294127.22521
581포천시포천시청(수도사업소)20090212운영중<NA>N공중이용시설업무시설경기도 포천시 중앙로61번길 9-6 (신읍동)경기도 포천시 신읍동 107-1번지48780537.892213127.197847
582하남시동서울골프장19940422운영중<NA>N공중이용시설업무시설경기도 하남시 감이로 317 (감이동)경기도 하남시 감이동 260-1번지46520037.496359127.168418
583하남시하남시청19930412운영중<NA>N공중이용시설업무시설경기도 하남시 대청로 10 (신장동)경기도 하남시 신장동 520번지46581037.539276127.214536
584하남시한강유역한경관리청20040706운영중<NA>N공중이용시설업무시설경기도 하남시 미사강변한강로 229경기도 하남시 망월동 231번지46515037.569847127.195497
585하남시한국도로공사20040706운영중<NA>N공중이용시설업무시설경기도 하남시 서하남로 88 (감일동)경기도 하남시 감일동 133-3번지46519037.51482127.153219
586화성시현대자동차(주)남양연구소19960325운영중<NA>N공중이용시설업무시설경기도 화성시 남양읍 현대연구소로 150 (장덕동)경기도 화성시 남양읍 장덕리 772-1번지44586937.159401126.813508