Overview

Dataset statistics

Number of variables6
Number of observations117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Text3
DateTime1
Categorical1

Dataset

Description대전광역시 서구 관내 행정사 업무신고한 사무소의 현황에 대한 데이터입니다.(사무소명, 소재지, 전화번호, 신고연월일)
URLhttps://www.data.go.kr/data/15028773/fileData.do

Alerts

비 고 has constant value ""Constant
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:16:34.564905
Analysis finished2023-12-12 19:16:35.497013
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T04:16:35.576002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.8
Q130
median59
Q388
95-th percentile111.2
Maximum117
Range116
Interquartile range (IQR)58

Descriptive statistics

Standard deviation33.919021
Coefficient of variation (CV)0.57489866
Kurtosis-1.2
Mean59
Median Absolute Deviation (MAD)29
Skewness0
Sum6903
Variance1150.5
MonotonicityStrictly increasing
2023-12-13T04:16:35.752892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
75 1
 
0.9%
87 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
117 1
0.9%
116 1
0.9%
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%

사무소명
Text

Distinct112
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:16:36.057155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.982906
Min length5

Characters and Unicode

Total characters1168
Distinct characters190
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)92.3%

Sample

1st row위드 행정사 사무소
2nd row샤크존경매행정사사무소
3rd rowYOU&I(유앤아이) 행정사 사무소
4th row행정사사무소 정음
5th row열린행정사사무소
ValueCountFrequency (%)
행정사 48
 
19.9%
사무소 44
 
18.3%
행정사사무소 11
 
4.6%
행정사무소 4
 
1.7%
고려행정사합동사무소 3
 
1.2%
번역·일반행정사 2
 
0.8%
윤성 2
 
0.8%
hk 2
 
0.8%
해성국제특허법률사무소 2
 
0.8%
법률사무소 2
 
0.8%
Other values (120) 121
50.2%
2023-12-13T04:16:36.500978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 195
16.7%
125
 
10.7%
정 109
 
9.3%
무 105
 
9.0%
소 104
 
8.9%
행 101
 
8.6%
이 14
 
1.2%
성 10
 
0.9%
국 10
 
0.9%
법 9
 
0.8%
Other values (180) 386
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1013
86.7%
Space Separator 125
 
10.7%
Uppercase Letter 19
 
1.6%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Other Punctuation 3
 
0.3%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 195
19.2%
정 109
 
10.8%
무 105
 
10.4%
소 104
 
10.3%
행 101
 
10.0%
이 14
 
1.4%
성 10
 
1.0%
국 10
 
1.0%
법 9
 
0.9%
대 9
 
0.9%
Other values (162) 347
34.3%
Uppercase Letter
ValueCountFrequency (%)
I 4
21.1%
Y 2
10.5%
O 2
10.5%
U 2
10.5%
H 2
10.5%
K 2
10.5%
M 1
 
5.3%
N 1
 
5.3%
V 1
 
5.3%
P 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
· 2
66.7%
& 1
33.3%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1012
86.6%
Common 136
 
11.6%
Latin 19
 
1.6%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 195
19.3%
정 109
 
10.8%
무 105
 
10.4%
소 104
 
10.3%
행 101
 
10.0%
이 14
 
1.4%
성 10
 
1.0%
국 10
 
1.0%
법 9
 
0.9%
대 9
 
0.9%
Other values (161) 346
34.2%
Latin
ValueCountFrequency (%)
I 4
21.1%
Y 2
10.5%
O 2
10.5%
U 2
10.5%
H 2
10.5%
K 2
10.5%
M 1
 
5.3%
N 1
 
5.3%
V 1
 
5.3%
P 1
 
5.3%
Common
ValueCountFrequency (%)
125
91.9%
( 3
 
2.2%
) 3
 
2.2%
· 2
 
1.5%
4 1
 
0.7%
2 1
 
0.7%
& 1
 
0.7%
Han
ValueCountFrequency (%)
鄭 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1012
86.6%
ASCII 153
 
13.1%
None 2
 
0.2%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 195
19.3%
정 109
 
10.8%
무 105
 
10.4%
소 104
 
10.3%
행 101
 
10.0%
이 14
 
1.4%
성 10
 
1.0%
국 10
 
1.0%
법 9
 
0.9%
대 9
 
0.9%
Other values (161) 346
34.2%
ASCII
ValueCountFrequency (%)
125
81.7%
I 4
 
2.6%
( 3
 
2.0%
) 3
 
2.0%
Y 2
 
1.3%
O 2
 
1.3%
U 2
 
1.3%
H 2
 
1.3%
K 2
 
1.3%
M 1
 
0.7%
Other values (7) 7
 
4.6%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
鄭 1
100.0%

소재지
Text

Distinct105
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:16:36.807133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length37.65812
Min length18

Characters and Unicode

Total characters4406
Distinct characters147
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

Unique97 ?
Unique (%)82.9%

Sample

1st row[35229]대전광역시 서구 대덕대로 223, 1008호 (둔산동)
2nd row[35259]대전광역시 서구 둔산중로 19, 샤크존상가 B198호 (탄방동)
3rd row[35289]대전광역시 서구 동서대로997번길 28(내동)
4th row[35262]대전광역시 서구 문정로2번길 123, 205호(탄방동, 둔산시티빌5)
5th row[35240]대전광역시 서구 둔산중로78번길 30, 202호(둔산동)
ValueCountFrequency (%)
서구 117
 
16.8%
둔산동 47
 
6.8%
35240]대전광역시 32
 
4.6%
둔산중로78번길 19
 
2.7%
35209]대전광역시 13
 
1.9%
둔산중로 11
 
1.6%
대덕대로 10
 
1.4%
35229]대전광역시 8
 
1.2%
월평동 8
 
1.2%
청사로 8
 
1.2%
Other values (282) 422
60.7%
2023-12-13T04:16:37.273017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
578
 
13.1%
3 224
 
5.1%
2 213
 
4.8%
5 172
 
3.9%
1 155
 
3.5%
0 153
 
3.5%
대 152
 
3.4%
동 139
 
3.2%
둔 121
 
2.7%
산 120
 
2.7%
Other values (137) 2379
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2015
45.7%
Decimal Number 1237
28.1%
Space Separator 578
 
13.1%
Open Punctuation 224
 
5.1%
Close Punctuation 224
 
5.1%
Other Punctuation 106
 
2.4%
Uppercase Letter 16
 
0.4%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 152
 
7.5%
동 139
 
6.9%
둔 121
 
6.0%
산 120
 
6.0%
서 119
 
5.9%
시 118
 
5.9%
역 118
 
5.9%
구 118
 
5.9%
전 117
 
5.8%
광 117
 
5.8%
Other values (113) 776
38.5%
Decimal Number
ValueCountFrequency (%)
3 224
18.1%
2 213
17.2%
5 172
13.9%
1 155
12.5%
0 153
12.4%
4 101
8.2%
6 58
 
4.7%
8 56
 
4.5%
9 54
 
4.4%
7 51
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 8
50.0%
R 3
 
18.8%
C 1
 
6.2%
F 1
 
6.2%
K 1
 
6.2%
D 1
 
6.2%
A 1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 112
50.0%
[ 112
50.0%
Close Punctuation
ValueCountFrequency (%)
] 112
50.0%
) 112
50.0%
Space Separator
ValueCountFrequency (%)
578
100.0%
Other Punctuation
ValueCountFrequency (%)
, 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2375
53.9%
Hangul 2015
45.7%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 152
 
7.5%
동 139
 
6.9%
둔 121
 
6.0%
산 120
 
6.0%
서 119
 
5.9%
시 118
 
5.9%
역 118
 
5.9%
구 118
 
5.9%
전 117
 
5.8%
광 117
 
5.8%
Other values (113) 776
38.5%
Common
ValueCountFrequency (%)
578
24.3%
3 224
 
9.4%
2 213
 
9.0%
5 172
 
7.2%
1 155
 
6.5%
0 153
 
6.4%
( 112
 
4.7%
[ 112
 
4.7%
] 112
 
4.7%
) 112
 
4.7%
Other values (7) 432
18.2%
Latin
ValueCountFrequency (%)
B 8
50.0%
R 3
 
18.8%
C 1
 
6.2%
F 1
 
6.2%
K 1
 
6.2%
D 1
 
6.2%
A 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2391
54.3%
Hangul 2015
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
578
24.2%
3 224
 
9.4%
2 213
 
8.9%
5 172
 
7.2%
1 155
 
6.5%
0 153
 
6.4%
( 112
 
4.7%
[ 112
 
4.7%
] 112
 
4.7%
) 112
 
4.7%
Other values (14) 448
18.7%
Hangul
ValueCountFrequency (%)
대 152
 
7.5%
동 139
 
6.9%
둔 121
 
6.0%
산 120
 
6.0%
서 119
 
5.9%
시 118
 
5.9%
역 118
 
5.9%
구 118
 
5.9%
전 117
 
5.8%
광 117
 
5.8%
Other values (113) 776
38.5%

전화번호
Text

Distinct60
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:16:37.525997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.6410256
Min length7

Characters and Unicode

Total characters1128
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)48.7%

Sample

1st row데이터 부존재
2nd row데이터 부존재
3rd row데이터 부존재
4th row데이터 부존재
5th row042-471-6774
ValueCountFrequency (%)
데이터 56
32.4%
부존재 56
32.4%
042-482-5330 2
 
1.2%
042-485-5513 2
 
1.2%
042-536-9009 1
 
0.6%
042-487-4774 1
 
0.6%
070-7532-3105 1
 
0.6%
042-487-9371 1
 
0.6%
042-489-7656 1
 
0.6%
042-482-2939 1
 
0.6%
Other values (51) 51
29.5%
2023-12-13T04:16:37.926117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 130
 
11.5%
- 122
 
10.8%
2 104
 
9.2%
0 96
 
8.5%
8 59
 
5.2%
이 56
 
5.0%
데 56
 
5.0%
재 56
 
5.0%
존 56
 
5.0%
부 56
 
5.0%
Other values (8) 337
29.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 614
54.4%
Other Letter 336
29.8%
Dash Punctuation 122
 
10.8%
Space Separator 56
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 130
21.2%
2 104
16.9%
0 96
15.6%
8 59
9.6%
5 50
 
8.1%
3 45
 
7.3%
7 41
 
6.7%
1 35
 
5.7%
9 31
 
5.0%
6 23
 
3.7%
Other Letter
ValueCountFrequency (%)
이 56
16.7%
데 56
16.7%
재 56
16.7%
존 56
16.7%
부 56
16.7%
터 56
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 792
70.2%
Hangul 336
29.8%

Most frequent character per script

Common
ValueCountFrequency (%)
4 130
16.4%
- 122
15.4%
2 104
13.1%
0 96
12.1%
8 59
7.4%
56
7.1%
5 50
 
6.3%
3 45
 
5.7%
7 41
 
5.2%
1 35
 
4.4%
Other values (2) 54
6.8%
Hangul
ValueCountFrequency (%)
이 56
16.7%
데 56
16.7%
재 56
16.7%
존 56
16.7%
부 56
16.7%
터 56
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 792
70.2%
Hangul 336
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 130
16.4%
- 122
15.4%
2 104
13.1%
0 96
12.1%
8 59
7.4%
56
7.1%
5 50
 
6.3%
3 45
 
5.7%
7 41
 
5.2%
1 35
 
4.4%
Other values (2) 54
6.8%
Hangul
ValueCountFrequency (%)
이 56
16.7%
데 56
16.7%
재 56
16.7%
존 56
16.7%
부 56
16.7%
터 56
16.7%

신고연월일
Date

Distinct101
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum1996-01-03 00:00:00
Maximum2023-07-12 00:00:00
2023-12-13T04:16:38.074678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:16:38.221509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비 고
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
영업중
117 

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 117
100.0%

Length

2023-12-13T04:16:38.349559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:16:38.455846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 117
100.0%

Interactions

2023-12-13T04:16:34.886297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:16:38.508217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호전화번호
일련번호1.0000.601
전화번호0.6011.000

Missing values

2023-12-13T04:16:35.356942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:16:35.456410image/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

일련번호사무소명소재지전화번호신고연월일비 고
01위드 행정사 사무소[35229]대전광역시 서구 대덕대로 223, 1008호 (둔산동)데이터 부존재2023-07-12영업중
12샤크존경매행정사사무소[35259]대전광역시 서구 둔산중로 19, 샤크존상가 B198호 (탄방동)데이터 부존재2023-05-16영업중
23YOU&I(유앤아이) 행정사 사무소[35289]대전광역시 서구 동서대로997번길 28(내동)데이터 부존재2023-03-20영업중
34행정사사무소 정음[35262]대전광역시 서구 문정로2번길 123, 205호(탄방동, 둔산시티빌5)데이터 부존재2023-03-16영업중
45열린행정사사무소[35240]대전광역시 서구 둔산중로78번길 30, 202호(둔산동)042-471-67742023-02-21영업중
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