Overview

Dataset statistics

Number of variables14
Number of observations30
Missing cells30
Missing cells (%)7.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory123.4 B

Variable types

Categorical5
Text6
Numeric2
Unsupported1

Dataset

Description샘플 데이터
Author오픈메이트
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=7

Alerts

기준_년월 has constant value ""Constant
말소_일자 has constant value ""Constant
주소_정제_구분자 is highly imbalanced (78.9%)Imbalance
등록_일자 has 30 (100.0%) missing valuesMissing
집객_시설_ID has unique valuesUnique
집객_시설_명 has unique valuesUnique
주소_코드 has unique valuesUnique
주소_명 has unique valuesUnique
엑스좌표_값 has unique valuesUnique
블록_코드 has unique valuesUnique
등록_일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 14:56:04.893392
Analysis finished2023-12-10 14:56:07.101147
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준_년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
201602
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201602
2nd row201602
3rd row201602
4th row201602
5th row201602

Common Values

ValueCountFrequency (%)
201602 30
100.0%

Length

2023-12-10T23:56:07.240923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:56:07.403854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201602 30
100.0%

집객_시설_구분_코드
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
103
18 
104
7 
102
2 
201
2 
202
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row104
2nd row103
3rd row103
4th row104
5th row104

Common Values

ValueCountFrequency (%)
103 18
60.0%
104 7
 
23.3%
102 2
 
6.7%
201 2
 
6.7%
202 1
 
3.3%

Length

2023-12-10T23:56:07.577686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:56:07.795344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
103 18
60.0%
104 7
 
23.3%
102 2
 
6.7%
201 2
 
6.7%
202 1
 
3.3%

집객_시설_코드
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
어린이집
11 
003001
6 
치과의원
4 
의원
4 
약국
4 

Length

Max length6
Median length5
Mean length3.8
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row치과의원
2nd row어린이집
3rd row의원
4th row어린이집
5th row003001

Common Values

ValueCountFrequency (%)
어린이집 11
36.7%
003001 6
20.0%
치과의원 4
 
13.3%
의원 4
 
13.3%
약국 4
 
13.3%
21 1
 
3.3%

Length

2023-12-10T23:56:08.050588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:56:08.349498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 11
36.7%
003001 6
20.0%
치과의원 4
 
13.3%
의원 4
 
13.3%
약국 4
 
13.3%
21 1
 
3.3%

집객_시설_ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:08.712757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.5333333
Min length6

Characters and Unicode

Total characters226
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row11550295
2nd row11580224
3rd row11847531
4th row12334235
5th rowA06220
ValueCountFrequency (%)
11550295 1
 
3.3%
11580224 1
 
3.3%
12832111 1
 
3.3%
c32678 1
 
3.3%
12933261 1
 
3.3%
s11315 1
 
3.3%
k05326 1
 
3.3%
12945366 1
 
3.3%
11865911 1
 
3.3%
11893044 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:56:09.319330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
27.0%
3 30
13.3%
2 28
12.4%
5 26
11.5%
8 17
 
7.5%
4 16
 
7.1%
9 13
 
5.8%
0 11
 
4.9%
6 10
 
4.4%
7 7
 
3.1%
Other values (4) 7
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 219
96.9%
Uppercase Letter 7
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61
27.9%
3 30
13.7%
2 28
12.8%
5 26
11.9%
8 17
 
7.8%
4 16
 
7.3%
9 13
 
5.9%
0 11
 
5.0%
6 10
 
4.6%
7 7
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
42.9%
C 2
28.6%
A 1
 
14.3%
K 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 219
96.9%
Latin 7
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61
27.9%
3 30
13.7%
2 28
12.8%
5 26
11.9%
8 17
 
7.8%
4 16
 
7.3%
9 13
 
5.9%
0 11
 
5.0%
6 10
 
4.6%
7 7
 
3.2%
Latin
ValueCountFrequency (%)
S 3
42.9%
C 2
28.6%
A 1
 
14.3%
K 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
27.0%
3 30
13.3%
2 28
12.4%
5 26
11.5%
8 17
 
7.5%
4 16
 
7.1%
9 13
 
5.8%
0 11
 
4.9%
6 10
 
4.4%
7 7
 
3.1%
Other values (4) 7
 
3.1%

집객_시설_명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:09.706231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.7333333
Min length4

Characters and Unicode

Total characters232
Distinct characters70
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row에*치*의*
2nd row대*중*교*
3rd row성*공*고*학*
4th row한*시*공* *실*영*(*외*
5th row대*민*정*외*의*
ValueCountFrequency (%)
에*치*의 1
 
3.0%
서*예*치*의 1
 
3.0%
예*피*과*원 1
 
3.0%
단*어*이 1
 
3.0%
서*신*현*우*취*국 1
 
3.0%
태*양*누*약 1
 
3.0%
파*텔*국 1
 
3.0%
한*랑*국 1
 
3.0%
미*어*이 1
 
3.0%
포 1
 
3.0%
Other values (23) 23
69.7%
2023-12-10T23:56:10.301206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 116
50.0%
이 6
 
2.6%
원 6
 
2.6%
의 5
 
2.2%
치 4
 
1.7%
어 4
 
1.7%
국 4
 
1.7%
3
 
1.3%
한 3
 
1.3%
양 3
 
1.3%
Other values (60) 78
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 116
50.0%
Other Letter 111
47.8%
Space Separator 3
 
1.3%
Uppercase Letter 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 6
 
5.4%
원 6
 
5.4%
의 5
 
4.5%
치 4
 
3.6%
어 4
 
3.6%
국 4
 
3.6%
한 3
 
2.7%
양 3
 
2.7%
은 3
 
2.7%
과 2
 
1.8%
Other values (56) 71
64.0%
Other Punctuation
ValueCountFrequency (%)
* 116
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
51.7%
Hangul 111
47.8%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 6
 
5.4%
원 6
 
5.4%
의 5
 
4.5%
치 4
 
3.6%
어 4
 
3.6%
국 4
 
3.6%
한 3
 
2.7%
양 3
 
2.7%
은 3
 
2.7%
과 2
 
1.8%
Other values (56) 71
64.0%
Common
ValueCountFrequency (%)
* 116
96.7%
3
 
2.5%
( 1
 
0.8%
Latin
ValueCountFrequency (%)
S 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
52.2%
Hangul 111
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 116
95.9%
3
 
2.5%
S 1
 
0.8%
( 1
 
0.8%
Hangul
ValueCountFrequency (%)
이 6
 
5.4%
원 6
 
5.4%
의 5
 
4.5%
치 4
 
3.6%
어 4
 
3.6%
국 4
 
3.6%
한 3
 
2.7%
양 3
 
2.7%
은 3
 
2.7%
과 2
 
1.8%
Other values (56) 71
64.0%

주소_코드
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:10.662216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters570
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row1*5*5*0*0*0*3*1*0*3
2nd row1*3*0*0*0*0*1*4*0*1
3rd row1*2*0*0*0*0*1*0*0*9
4th row1*5*0*0*0*0*0*2*0*2
5th row1*5*0*0*0*0*6*6*0*7
ValueCountFrequency (%)
1*5*5*0*0*0*3*1*0*3 1
 
3.3%
1*3*0*0*0*0*1*4*0*1 1
 
3.3%
1*6*0*0*0*0*2*5*0*3 1
 
3.3%
1*7*0*0*0*0*4*7*0*3 1
 
3.3%
1*3*0*1*0*0*0*1*0*0 1
 
3.3%
1*3*0*0*0*0*6*0*0*2 1
 
3.3%
1*2*0*1*0*0*0*6*0*0 1
 
3.3%
1*6*0*0*0*0*8*1*0*2 1
 
3.3%
1*5*5*0*0*0*9*8*0*4 1
 
3.3%
1*2*0*3*0*0*0*7*0*6 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:56:11.220694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 270
47.4%
0 158
27.7%
1 53
 
9.3%
3 17
 
3.0%
2 16
 
2.8%
5 14
 
2.5%
6 14
 
2.5%
7 10
 
1.8%
9 8
 
1.4%
4 5
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
52.6%
Other Punctuation 270
47.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 158
52.7%
1 53
 
17.7%
3 17
 
5.7%
2 16
 
5.3%
5 14
 
4.7%
6 14
 
4.7%
7 10
 
3.3%
9 8
 
2.7%
4 5
 
1.7%
8 5
 
1.7%
Other Punctuation
ValueCountFrequency (%)
* 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 270
47.4%
0 158
27.7%
1 53
 
9.3%
3 17
 
3.0%
2 16
 
2.8%
5 14
 
2.5%
6 14
 
2.5%
7 10
 
1.8%
9 8
 
1.4%
4 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 270
47.4%
0 158
27.7%
1 53
 
9.3%
3 17
 
3.0%
2 16
 
2.8%
5 14
 
2.5%
6 14
 
2.5%
7 10
 
1.8%
9 8
 
1.4%
4 5
 
0.9%

주소_명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:11.610373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length42
Mean length30.1
Min length18

Characters and Unicode

Total characters903
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row서**별**동** **대**2**길**5**
2nd row서**별**종** ** **5** ** **로**)**
3rd row서**별**영**구**의** **번**
4th row서**별**서**구**일**4**-**(**동**
5th row서**별**강** **로**3**2**(**동**안**)**
ValueCountFrequency (%)
서**별**강 7
 
9.7%
5
 
6.9%
서**별**동 2
 
2.8%
당 2
 
2.8%
서**별**성 2
 
2.8%
서**별**서 2
 
2.8%
6 1
 
1.4%
로**길 1
 
1.4%
서**별**은 1
 
1.4%
2**1**4**메**프**동**0**5**호**진 1
 
1.4%
Other values (48) 48
66.7%
2023-12-10T23:56:12.190073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 602
66.7%
42
 
4.7%
서 37
 
4.1%
별 27
 
3.0%
동 15
 
1.7%
4 11
 
1.2%
2 9
 
1.0%
길 9
 
1.0%
구 8
 
0.9%
3 8
 
0.9%
Other values (61) 135
 
15.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 608
67.3%
Other Letter 181
 
20.0%
Decimal Number 51
 
5.6%
Space Separator 42
 
4.7%
Open Punctuation 8
 
0.9%
Close Punctuation 8
 
0.9%
Dash Punctuation 4
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 37
20.4%
별 27
14.9%
동 15
 
8.3%
길 9
 
5.0%
구 8
 
4.4%
강 8
 
4.4%
로 7
 
3.9%
층 4
 
2.2%
호 3
 
1.7%
성 3
 
1.7%
Other values (44) 60
33.1%
Decimal Number
ValueCountFrequency (%)
4 11
21.6%
2 9
17.6%
3 8
15.7%
1 7
13.7%
5 7
13.7%
0 5
9.8%
9 2
 
3.9%
6 1
 
2.0%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
* 602
99.0%
, 5
 
0.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
80.0%
Hangul 181
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 37
20.4%
별 27
14.9%
동 15
 
8.3%
길 9
 
5.0%
구 8
 
4.4%
강 8
 
4.4%
로 7
 
3.9%
층 4
 
2.2%
호 3
 
1.7%
성 3
 
1.7%
Other values (44) 60
33.1%
Common
ValueCountFrequency (%)
* 602
83.4%
42
 
5.8%
4 11
 
1.5%
2 9
 
1.2%
3 8
 
1.1%
( 8
 
1.1%
) 8
 
1.1%
1 7
 
1.0%
5 7
 
1.0%
0 5
 
0.7%
Other values (7) 15
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
80.0%
Hangul 181
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 602
83.4%
42
 
5.8%
4 11
 
1.5%
2 9
 
1.2%
3 8
 
1.1%
( 8
 
1.1%
) 8
 
1.1%
1 7
 
1.0%
5 7
 
1.0%
0 5
 
0.7%
Other values (7) 15
 
2.1%
Hangul
ValueCountFrequency (%)
서 37
20.4%
별 27
14.9%
동 15
 
8.3%
길 9
 
5.0%
구 8
 
4.4%
강 8
 
4.4%
로 7
 
3.9%
층 4
 
2.2%
호 3
 
1.7%
성 3
 
1.7%
Other values (44) 60
33.1%

전화번호
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:12.482612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.966667
Min length8

Characters and Unicode

Total characters329
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

Unique26 ?
Unique (%)86.7%

Sample

1st row02-**8-**19
2nd row02-**4-**88
3rd row02-**3-**59
4th row02-**3-**75
5th row02-**0-**75
ValueCountFrequency (%)
02-**2-**75 2
 
6.7%
02-**4-**88 2
 
6.7%
02-**8-**19 1
 
3.3%
445-**39 1
 
3.3%
02-**6-**75 1
 
3.3%
02-**6-**67 1
 
3.3%
593-**83 1
 
3.3%
02-**34-**90 1
 
3.3%
02-**7-**88 1
 
3.3%
02-**77-**11 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:56:13.019138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 114
34.7%
- 57
17.3%
2 35
 
10.6%
0 33
 
10.0%
8 16
 
4.9%
7 15
 
4.6%
5 14
 
4.3%
3 11
 
3.3%
9 10
 
3.0%
4 9
 
2.7%
Other values (2) 15
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 158
48.0%
Other Punctuation 114
34.7%
Dash Punctuation 57
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 35
22.2%
0 33
20.9%
8 16
10.1%
7 15
9.5%
5 14
 
8.9%
3 11
 
7.0%
9 10
 
6.3%
4 9
 
5.7%
1 8
 
5.1%
6 7
 
4.4%
Other Punctuation
ValueCountFrequency (%)
* 114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 114
34.7%
- 57
17.3%
2 35
 
10.6%
0 33
 
10.0%
8 16
 
4.9%
7 15
 
4.6%
5 14
 
4.3%
3 11
 
3.3%
9 10
 
3.0%
4 9
 
2.7%
Other values (2) 15
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 114
34.7%
- 57
17.3%
2 35
 
10.6%
0 33
 
10.0%
8 16
 
4.9%
7 15
 
4.6%
5 14
 
4.3%
3 11
 
3.3%
9 10
 
3.0%
4 9
 
2.7%
Other values (2) 15
 
4.6%

엑스좌표_값
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198345.07
Minimum185386
Maximum213578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:56:13.214571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185386
5-th percentile187797.5
Q1192707.75
median197122
Q3204751.25
95-th percentile209695.95
Maximum213578
Range28192
Interquartile range (IQR)12043.5

Descriptive statistics

Standard deviation7560.8617
Coefficient of variation (CV)0.038119736
Kurtosis-0.96906799
Mean198345.07
Median Absolute Deviation (MAD)5854.5
Skewness0.16447885
Sum5950352
Variance57166629
MonotonicityNot monotonic
2023-12-10T23:56:13.418206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
190857 1
 
3.3%
196839 1
 
3.3%
192827 1
 
3.3%
195667 1
 
3.3%
202313 1
 
3.3%
204791 1
 
3.3%
194222 1
 
3.3%
190996 1
 
3.3%
207282 1
 
3.3%
195351 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
185386 1
3.3%
187640 1
3.3%
187990 1
3.3%
188508 1
3.3%
190857 1
3.3%
190996 1
3.3%
191539 1
3.3%
192668 1
3.3%
192827 1
3.3%
192944 1
3.3%
ValueCountFrequency (%)
213578 1
3.3%
211050 1
3.3%
208041 1
3.3%
207282 1
3.3%
206598 1
3.3%
205526 1
3.3%
205013 1
3.3%
204791 1
3.3%
204632 1
3.3%
202640 1
3.3%

와이좌표_값
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448289.93
Minimum441717
Maximum461780
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:56:13.602312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441717
5-th percentile442058
Q1444418
median447919.5
Q3449883.75
95-th percentile458355.1
Maximum461780
Range20063
Interquartile range (IQR)5465.75

Descriptive statistics

Standard deviation5089.5129
Coefficient of variation (CV)0.011353172
Kurtosis1.3695934
Mean448289.93
Median Absolute Deviation (MAD)2647
Skewness1.0832082
Sum13448698
Variance25903142
MonotonicityNot monotonic
2023-12-10T23:56:13.773098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
444418 2
 
6.7%
442899 1
 
3.3%
445950 1
 
3.3%
448231 1
 
3.3%
454398 1
 
3.3%
445796 1
 
3.3%
443693 1
 
3.3%
454625 1
 
3.3%
448710 1
 
3.3%
449637 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
441717 1
3.3%
441887 1
3.3%
442267 1
3.3%
442799 1
3.3%
442899 1
3.3%
443331 1
3.3%
443693 1
3.3%
444418 2
6.7%
445796 1
3.3%
445950 1
3.3%
ValueCountFrequency (%)
461780 1
3.3%
461407 1
3.3%
454625 1
3.3%
454398 1
3.3%
452843 1
3.3%
450593 1
3.3%
450540 1
3.3%
449885 1
3.3%
449880 1
3.3%
449843 1
3.3%

주소_정제_구분자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
29 
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
96.7%
6 1
 
3.3%

Length

2023-12-10T23:56:14.002141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:56:14.175012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
96.7%
6 1
 
3.3%

블록_코드
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:56:14.431148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.7666667
Min length5

Characters and Unicode

Total characters173
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row1*7*6*
2nd row2*2*1
3rd row2*3*6*
4th row3*3*4*
5th row2*9*1*
ValueCountFrequency (%)
1*7*6 1
 
3.3%
2*2*1 1
 
3.3%
2*8*7 1
 
3.3%
4*1*5 1
 
3.3%
1*3*3 1
 
3.3%
2*4*0 1
 
3.3%
1*9*8 1
 
3.3%
4*8*1 1
 
3.3%
1*4*6 1
 
3.3%
2*0*3 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:56:14.898721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 83
48.0%
2 16
 
9.2%
3 16
 
9.2%
1 14
 
8.1%
4 11
 
6.4%
6 9
 
5.2%
7 7
 
4.0%
5 5
 
2.9%
9 4
 
2.3%
8 4
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
52.0%
Other Punctuation 83
48.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16
17.8%
3 16
17.8%
1 14
15.6%
4 11
12.2%
6 9
10.0%
7 7
7.8%
5 5
 
5.6%
9 4
 
4.4%
8 4
 
4.4%
0 4
 
4.4%
Other Punctuation
ValueCountFrequency (%)
* 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 83
48.0%
2 16
 
9.2%
3 16
 
9.2%
1 14
 
8.1%
4 11
 
6.4%
6 9
 
5.2%
7 7
 
4.0%
5 5
 
2.9%
9 4
 
2.3%
8 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 83
48.0%
2 16
 
9.2%
3 16
 
9.2%
1 14
 
8.1%
4 11
 
6.4%
6 9
 
5.2%
7 7
 
4.0%
5 5
 
2.9%
9 4
 
2.3%
8 4
 
2.3%

등록_일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

말소_일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
20160630
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20160630
2nd row20160630
3rd row20160630
4th row20160630
5th row20160630

Common Values

ValueCountFrequency (%)
20160630 30
100.0%

Length

2023-12-10T23:56:15.100685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:56:15.272007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20160630 30
100.0%

Interactions

2023-12-10T23:56:06.085387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:56:05.738585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:56:06.269212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:56:05.913848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:56:15.402703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집객_시설_구분_코드집객_시설_코드집객_시설_ID집객_시설_명주소_코드주소_명전화번호엑스좌표_값와이좌표_값주소_정제_구분자블록_코드
집객_시설_구분_코드1.0000.2861.0001.0001.0001.0000.4580.0000.4690.0001.000
집객_시설_코드0.2861.0001.0001.0001.0001.0000.8350.0000.0000.3651.000
집객_시설_ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
집객_시설_명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소_코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소_명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호0.4580.8351.0001.0001.0001.0001.0000.0000.9351.0001.000
엑스좌표_값0.0000.0001.0001.0001.0001.0000.0001.0000.3380.0001.000
와이좌표_값0.4690.0001.0001.0001.0001.0000.9350.3381.0000.0001.000
주소_정제_구분자0.0000.3651.0001.0001.0001.0001.0000.0000.0001.0001.000
블록_코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-10T23:56:15.592090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집객_시설_코드집객_시설_구분_코드주소_정제_구분자
집객_시설_코드1.0000.1770.231
집객_시설_구분_코드0.1771.0000.000
주소_정제_구분자0.2310.0001.000
2023-12-10T23:56:15.805320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
엑스좌표_값와이좌표_값집객_시설_구분_코드집객_시설_코드주소_정제_구분자
엑스좌표_값1.0000.2220.0000.0000.000
와이좌표_값0.2221.0000.2600.0000.000
집객_시설_구분_코드0.0000.2601.0000.1770.000
집객_시설_코드0.0000.0000.1771.0000.231
주소_정제_구분자0.0000.0000.0000.2311.000

Missing values

2023-12-10T23:56:06.548910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:56:06.939651image/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.

Sample

기준_년월집객_시설_구분_코드집객_시설_코드집객_시설_ID집객_시설_명주소_코드주소_명전화번호엑스좌표_값와이좌표_값주소_정제_구분자블록_코드등록_일자말소_일자
0201602104치과의원11550295에*치*의*1*5*5*0*0*0*3*1*0*3서**별**동** **대**2**길**5**02-**8-**1919085744289911*7*6*<NA>20160630
1201602103어린이집11580224대*중*교*1*3*0*0*0*0*1*4*0*1서**별**종** ** **5** ** **로**)**02-**4-**8820132246178012*2*1<NA>20160630
2201602103의원11847531성*공*고*학*1*2*0*0*0*0*1*0*0*9서**별**영**구**의** **번**02-**3-**5918850844188712*3*6*<NA>20160630
3201602104어린이집12334235한*시*공* *실*영*(*외*1*5*0*0*0*0*0*2*0*2서**별**서**구**일**4**-**(**동**02-**3-**7519153945059313*3*4*<NA>20160630
4201602104003001A06220대*민*정*외*의*1*5*0*0*0*0*6*6*0*7서**별**강** **로**3**2**(**동**안**)**02-**0-**7518799044279912*9*1*<NA>20160630
5201602104어린이집11389257마*스*치*의*1*5*0*0*0*0*0*6*0*1서**별**강** **로**4**3**(**동**02-**60-**7520248144441812*6*2*<NA>20160630
6201602103약국11335262권*과*원*1*2*0*3*0*0*2*3*0*0서**별**서**구**아**4**9**02-**2-**7519947545054013*3*5<NA>20160630
7201602103어린이집11572531양*구*1*5*0*0*0*0*1*9*0*0서**별**강** **대**1**5**층**성**,**빌**02-**2-**9718764044667711*7*8<NA>20160630
8201602104어린이집11518031럭*약*1*3*0*0*0*0*7*4*0*0서**별**강** **개**길**0**0**1** **서**02-**6-**2220264044333113*2*6*<NA>20160630
9201602102의원814195더*리*사*드*호*1*6*0*0*0*0*8*2*0*9서**별**강** **면**2** ** **호**02-**4-**8821105044611813*0*5*<NA>20160630
기준_년월집객_시설_구분_코드집객_시설_코드집객_시설_ID집객_시설_명주소_코드주소_명전화번호엑스좌표_값와이좌표_값주소_정제_구분자블록_코드등록_일자말소_일자
20201602103의원11869844이*영*원*1*5*0*0*0*0*6*0*0*2서**별**관** **길**0**2**호**봉**,**악**타**산**)**02-**5-**3818538644988014*6*4*<NA>20160630
21201602103치과의원11893044S*은* *포*1*2*0*3*0*0*0*7*0*6서**별**송** **로**길** **02-**99-**0020501344760812*0*3*<NA>20160630
22201602104약국11865911미*어*이*1*5*5*0*0*0*9*8*0*4서**별**영**구**지** **0**빌**층**사**린**02-**2-**1119535144963711*4*6*<NA>20160630
232016022012112945366한*랑*국*1*6*0*0*0*0*8*1*0*2서**별**서** **당**1** **1**(**동**동**차**)**02-**77-**1120728244871014*8*1*<NA>20160630
24201602103약국K05326파*텔*국*1*2*0*1*0*0*0*6*0*0서**별**동**구**산**9** **5**(**동**니**딩**02-**7-**8819099645462511*9*8<NA>20160630
25201602103003001S11315태*양*누*약*1*3*0*0*0*0*6*0*0*2서**별**동** **로**길**2**상**.**초**교**02-**34-**9019422244369312*4*0<NA>20160630
26201602103약국12933261서*신*현*우*취*국*1*3*0*1*0*0*0*1*0*0서**별**서**구**희**4** **은**593-**8320479144579661*3*3*<NA>20160630
27201602103003001C32678단*어*이*1*7*0*0*0*0*4*7*0*3서**별**강** **로**길**4**2**덕** **6**)**02-**6-**6720231345439814*1*5*<NA>20160630
28201602103의원12832111예*피*과*원*1*6*0*0*0*0*2*5*0*3서**금** **본**8**-**02-**6-**7519566744823112*8*7<NA>20160630
2920160210200300111346124신*방*연*국*1*7*0*1*0*0*1*2*0*4서**별**마** **로**3**4**(**동**교**)**02-**45-**1619282744441813*6*7*<NA>20160630