Overview

Dataset statistics

Number of variables8
Number of observations122
Missing cells40
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory66.1 B

Variable types

Numeric1
Categorical3
Text3
DateTime1

Dataset

Description남양주시 행정사사무소 데이터로 상호명,신고일자,소재지 주소(지번,도로명),위도,경도,전화번호 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15030007/fileData.do

Alerts

시군명 has constant value ""Constant
운영상태 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전화번호 has 40 (32.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:20:28.082408
Analysis finished2023-12-12 12:20:28.730013
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.5
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:20:28.826477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.05
Q131.25
median61.5
Q391.75
95-th percentile115.95
Maximum122
Range121
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation35.362409
Coefficient of variation (CV)0.57499853
Kurtosis-1.2
Mean61.5
Median Absolute Deviation (MAD)30.5
Skewness0
Sum7503
Variance1250.5
MonotonicityStrictly increasing
2023-12-12T21:20:29.015486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
93 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
경기도 남양주시
122 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 남양주시
2nd row경기도 남양주시
3rd row경기도 남양주시
4th row경기도 남양주시
5th row경기도 남양주시

Common Values

ValueCountFrequency (%)
경기도 남양주시 122
100.0%

Length

2023-12-12T21:20:29.178766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:20:29.304636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 122
50.0%
남양주시 122
50.0%

상호명
Text

Distinct115
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T21:20:29.603660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length9.4180328
Min length5

Characters and Unicode

Total characters1149
Distinct characters168
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)92.6%

Sample

1st row행정사 양승원사무소
2nd row행정사 합동사무소 인송
3rd row행정사 합동사무소 인송
4th row행정사 합동사무소 인송
5th row행정사 합동사무소 인송
ValueCountFrequency (%)
행정사 45
 
19.7%
행정사사무소 29
 
12.7%
사무소 17
 
7.4%
김앤드정토지보상전문 5
 
2.2%
행정사합동사무소 5
 
2.2%
합동사무소 4
 
1.7%
인송 4
 
1.7%
에스앤케이 2
 
0.9%
경기행정사사무소 1
 
0.4%
정성진 1
 
0.4%
Other values (116) 116
50.7%
2023-12-12T21:20:30.106762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 209
18.2%
정 133
 
11.6%
행 123
 
10.7%
107
 
9.3%
무 92
 
8.0%
소 90
 
7.8%
김 17
 
1.5%
동 14
 
1.2%
이 12
 
1.0%
성 10
 
0.9%
Other values (158) 342
29.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1020
88.8%
Space Separator 107
 
9.3%
Lowercase Letter 11
 
1.0%
Uppercase Letter 9
 
0.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 209
20.5%
정 133
13.0%
행 123
 
12.1%
무 92
 
9.0%
소 90
 
8.8%
김 17
 
1.7%
동 14
 
1.4%
이 12
 
1.2%
성 10
 
1.0%
합 9
 
0.9%
Other values (137) 311
30.5%
Lowercase Letter
ValueCountFrequency (%)
r 2
18.2%
a 2
18.2%
m 1
9.1%
o 1
9.1%
f 1
9.1%
t 1
9.1%
l 1
9.1%
n 1
9.1%
b 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
K 1
11.1%
G 1
11.1%
M 1
11.1%
T 1
11.1%
E 1
11.1%
J 1
11.1%
S 1
11.1%
P 1
11.1%
U 1
11.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1020
88.8%
Common 109
 
9.5%
Latin 20
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 209
20.5%
정 133
13.0%
행 123
 
12.1%
무 92
 
9.0%
소 90
 
8.8%
김 17
 
1.7%
동 14
 
1.4%
이 12
 
1.2%
성 10
 
1.0%
합 9
 
0.9%
Other values (137) 311
30.5%
Latin
ValueCountFrequency (%)
r 2
 
10.0%
a 2
 
10.0%
K 1
 
5.0%
G 1
 
5.0%
M 1
 
5.0%
T 1
 
5.0%
E 1
 
5.0%
J 1
 
5.0%
S 1
 
5.0%
m 1
 
5.0%
Other values (8) 8
40.0%
Common
ValueCountFrequency (%)
107
98.2%
( 1
 
0.9%
) 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1020
88.8%
ASCII 129
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 209
20.5%
정 133
13.0%
행 123
 
12.1%
무 92
 
9.0%
소 90
 
8.8%
김 17
 
1.7%
동 14
 
1.4%
이 12
 
1.2%
성 10
 
1.0%
합 9
 
0.9%
Other values (137) 311
30.5%
ASCII
ValueCountFrequency (%)
107
82.9%
r 2
 
1.6%
a 2
 
1.6%
K 1
 
0.8%
G 1
 
0.8%
M 1
 
0.8%
T 1
 
0.8%
E 1
 
0.8%
J 1
 
0.8%
S 1
 
0.8%
Other values (11) 11
 
8.5%

신고일자
Date

Distinct107
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1995-10-25 00:00:00
Maximum2022-01-07 00:00:00
2023-12-12T21:20:30.318862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:20:30.491486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지 주소
Text

Distinct111
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T21:20:30.753796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39.5
Mean length29.278689
Min length16

Characters and Unicode

Total characters3572
Distinct characters178
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)86.1%

Sample

1st row경기도 남양주시 다산중앙로82번안길 160109호(다산동)
2nd row경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)
3rd row경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)
4th row경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)
5th row경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)
ValueCountFrequency (%)
경기도 122
 
17.9%
남양주시 122
 
17.9%
화도읍 20
 
2.9%
진접읍 16
 
2.3%
금곡동 15
 
2.2%
경춘로 11
 
1.6%
다산동 9
 
1.3%
와부읍 9
 
1.3%
장현리 8
 
1.2%
1호 7
 
1.0%
Other values (259) 344
50.4%
2023-12-12T21:20:31.185379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
561
 
15.7%
1 176
 
4.9%
도 146
 
4.1%
경 144
 
4.0%
남 135
 
3.8%
양 135
 
3.8%
주 131
 
3.7%
시 122
 
3.4%
기 122
 
3.4%
0 94
 
2.6%
Other values (168) 1806
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2163
60.6%
Decimal Number 707
 
19.8%
Space Separator 561
 
15.7%
Close Punctuation 54
 
1.5%
Open Punctuation 54
 
1.5%
Dash Punctuation 31
 
0.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 146
 
6.7%
경 144
 
6.7%
남 135
 
6.2%
양 135
 
6.2%
주 131
 
6.1%
시 122
 
5.6%
기 122
 
5.6%
로 85
 
3.9%
호 85
 
3.9%
동 81
 
3.7%
Other values (152) 977
45.2%
Decimal Number
ValueCountFrequency (%)
1 176
24.9%
0 94
13.3%
2 88
12.4%
3 70
 
9.9%
4 67
 
9.5%
6 54
 
7.6%
7 43
 
6.1%
5 43
 
6.1%
9 38
 
5.4%
8 34
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2163
60.6%
Common 1407
39.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 146
 
6.7%
경 144
 
6.7%
남 135
 
6.2%
양 135
 
6.2%
주 131
 
6.1%
시 122
 
5.6%
기 122
 
5.6%
로 85
 
3.9%
호 85
 
3.9%
동 81
 
3.7%
Other values (152) 977
45.2%
Common
ValueCountFrequency (%)
561
39.9%
1 176
 
12.5%
0 94
 
6.7%
2 88
 
6.3%
3 70
 
5.0%
4 67
 
4.8%
6 54
 
3.8%
) 54
 
3.8%
( 54
 
3.8%
7 43
 
3.1%
Other values (4) 146
 
10.4%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2163
60.6%
ASCII 1409
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
561
39.8%
1 176
 
12.5%
0 94
 
6.7%
2 88
 
6.2%
3 70
 
5.0%
4 67
 
4.8%
6 54
 
3.8%
) 54
 
3.8%
( 54
 
3.8%
7 43
 
3.1%
Other values (6) 148
 
10.5%
Hangul
ValueCountFrequency (%)
도 146
 
6.7%
경 144
 
6.7%
남 135
 
6.2%
양 135
 
6.2%
주 131
 
6.1%
시 122
 
5.6%
기 122
 
5.6%
로 85
 
3.9%
호 85
 
3.9%
동 81
 
3.7%
Other values (152) 977
45.2%

전화번호
Text

MISSING 

Distinct74
Distinct (%)90.2%
Missing40
Missing (%)32.8%
Memory size1.1 KiB
2023-12-12T21:20:31.452092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.036585
Min length12

Characters and Unicode

Total characters987
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

Unique71 ?
Unique (%)86.6%

Sample

1st row031-555-6565
2nd row031-592-3533
3rd row031-592-3533
4th row031-592-3533
5th row031-592-3533
ValueCountFrequency (%)
031-528-5479 5
 
6.1%
031-592-3533 4
 
4.9%
031-511-4001 2
 
2.4%
031-527-1477 1
 
1.2%
031-592-7105 1
 
1.2%
031-592-9966 1
 
1.2%
031-511-4300 1
 
1.2%
031-594-6755 1
 
1.2%
031-595-2300 1
 
1.2%
031-557-6007 1
 
1.2%
Other values (64) 64
78.0%
2023-12-12T21:20:31.868641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 164
16.6%
1 147
14.9%
0 129
13.1%
5 127
12.9%
3 125
12.7%
7 65
 
6.6%
2 60
 
6.1%
9 59
 
6.0%
8 39
 
4.0%
4 36
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 823
83.4%
Dash Punctuation 164
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 147
17.9%
0 129
15.7%
5 127
15.4%
3 125
15.2%
7 65
7.9%
2 60
7.3%
9 59
7.2%
8 39
 
4.7%
4 36
 
4.4%
6 36
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 987
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 164
16.6%
1 147
14.9%
0 129
13.1%
5 127
12.9%
3 125
12.7%
7 65
 
6.6%
2 60
 
6.1%
9 59
 
6.0%
8 39
 
4.0%
4 36
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 164
16.6%
1 147
14.9%
0 129
13.1%
5 127
12.9%
3 125
12.7%
7 65
 
6.6%
2 60
 
6.1%
9 59
 
6.0%
8 39
 
4.0%
4 36
 
3.6%

운영상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업중
122 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 122
100.0%

Length

2023-12-12T21:20:32.027992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:20:32.139993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 122
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022-01-01
122 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-01-01
2nd row2022-01-01
3rd row2022-01-01
4th row2022-01-01
5th row2022-01-01

Common Values

ValueCountFrequency (%)
2022-01-01 122
100.0%

Length

2023-12-12T21:20:32.262785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:20:32.394429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-01-01 122
100.0%

Interactions

2023-12-12T21:20:28.405421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:20:32.467924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호
연번1.0000.982
전화번호0.9821.000

Missing values

2023-12-12T21:20:28.556557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:20:28.676850image/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

연번시군명상호명신고일자소재지 주소전화번호운영상태데이터기준일자
01경기도 남양주시행정사 양승원사무소2022-01-07경기도 남양주시 다산중앙로82번안길 160109호(다산동)031-555-6565영업중2022-01-01
12경기도 남양주시행정사 합동사무소 인송2022-01-04경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)031-592-3533영업중2022-01-01
23경기도 남양주시행정사 합동사무소 인송2022-01-04경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)031-592-3533영업중2022-01-01
34경기도 남양주시행정사 합동사무소 인송2022-01-04경기도 남양주시 경춘로 979양주빌딩 6층 (금곡동)031-592-3533영업중2022-01-01
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