Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells2
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory46.5 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구의 세무사 사무소에 대한 데이터입니다. 상호명, 도로명주소, 전화번호 등의 항목을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15087029/fileData.do

Alerts

전화번호 has 2 (8.3%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:02:58.581782
Analysis finished2023-12-12 22:02:59.036227
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T07:02:59.102736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-13T07:02:59.217380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

상호명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T07:02:59.433664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.5833333
Min length6

Characters and Unicode

Total characters230
Distinct characters61
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row세무사신현배사무소
2nd row하석용 김태웅 세무사 사무소
3rd row세무사최상동사무소
4th row김주택세무사사무소
5th row다율세무법인
ValueCountFrequency (%)
세무사신현배사무소 1
 
3.4%
선우세무회계사무소 1
 
3.4%
법무사 1
 
3.4%
세무회계사설삼환사무소 1
 
3.4%
세무사김재헌사무소 1
 
3.4%
윤인섭세무회계사무소 1
 
3.4%
오암세무회계사무소 1
 
3.4%
세무사최효주사무소 1
 
3.4%
김태웅세무회계사무소 1
 
3.4%
윤영자세무회계사무소 1
 
3.4%
Other values (19) 19
65.5%
2023-12-13T07:02:59.811074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
무 45
19.6%
사 34
14.8%
세 22
 
9.6%
소 22
 
9.6%
계 13
 
5.7%
회 13
 
5.7%
5
 
2.2%
김 5
 
2.2%
인 5
 
2.2%
유 3
 
1.3%
Other values (51) 63
27.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 225
97.8%
Space Separator 5
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 45
20.0%
사 34
15.1%
세 22
 
9.8%
소 22
 
9.8%
계 13
 
5.8%
회 13
 
5.8%
김 5
 
2.2%
인 5
 
2.2%
유 3
 
1.3%
법 3
 
1.3%
Other values (50) 60
26.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 225
97.8%
Common 5
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 45
20.0%
사 34
15.1%
세 22
 
9.8%
소 22
 
9.8%
계 13
 
5.8%
회 13
 
5.8%
김 5
 
2.2%
인 5
 
2.2%
유 3
 
1.3%
법 3
 
1.3%
Other values (50) 60
26.7%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 225
97.8%
ASCII 5
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
무 45
20.0%
사 34
15.1%
세 22
 
9.8%
소 22
 
9.8%
계 13
 
5.8%
회 13
 
5.8%
김 5
 
2.2%
인 5
 
2.2%
유 3
 
1.3%
법 3
 
1.3%
Other values (50) 60
26.7%
ASCII
ValueCountFrequency (%)
5
100.0%

지번주소
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T07:03:00.045645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length22.958333
Min length14

Characters and Unicode

Total characters551
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row인천광역시 미추홀구 숭의동 407-1
2nd row인천광역시 미추홀구 숭의동 163-6 하나은행 3층
3rd row인천광역시 미추홀구 주안동 989-1
4th row인천광역시 미추홀구 주안동 1532-5
5th row인천광역시 미추홀구 학익동 244-33
ValueCountFrequency (%)
인천광역시 24
22.4%
미추홀구 24
22.4%
숭의동 9
 
8.4%
주안동 7
 
6.5%
학익동 6
 
5.6%
989-1 4
 
3.7%
르네상스빌딩 2
 
1.9%
용현동 2
 
1.9%
160-21 1
 
0.9%
숭의빌딩 1
 
0.9%
Other values (27) 27
25.2%
2023-12-13T07:03:00.459448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
15.4%
1 25
 
4.5%
동 25
 
4.5%
인 24
 
4.4%
추 24
 
4.4%
구 24
 
4.4%
홀 24
 
4.4%
천 24
 
4.4%
미 24
 
4.4%
시 24
 
4.4%
Other values (40) 248
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 325
59.0%
Decimal Number 118
 
21.4%
Space Separator 85
 
15.4%
Dash Punctuation 21
 
3.8%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
 
7.7%
인 24
 
7.4%
추 24
 
7.4%
구 24
 
7.4%
홀 24
 
7.4%
천 24
 
7.4%
미 24
 
7.4%
시 24
 
7.4%
역 24
 
7.4%
광 24
 
7.4%
Other values (26) 84
25.8%
Decimal Number
ValueCountFrequency (%)
1 25
21.2%
2 17
14.4%
4 14
11.9%
5 14
11.9%
3 12
10.2%
9 11
9.3%
0 8
 
6.8%
6 8
 
6.8%
8 7
 
5.9%
7 2
 
1.7%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 325
59.0%
Common 226
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
 
7.7%
인 24
 
7.4%
추 24
 
7.4%
구 24
 
7.4%
홀 24
 
7.4%
천 24
 
7.4%
미 24
 
7.4%
시 24
 
7.4%
역 24
 
7.4%
광 24
 
7.4%
Other values (26) 84
25.8%
Common
ValueCountFrequency (%)
85
37.6%
1 25
 
11.1%
- 21
 
9.3%
2 17
 
7.5%
4 14
 
6.2%
5 14
 
6.2%
3 12
 
5.3%
9 11
 
4.9%
0 8
 
3.5%
6 8
 
3.5%
Other values (4) 11
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 325
59.0%
ASCII 226
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
37.6%
1 25
 
11.1%
- 21
 
9.3%
2 17
 
7.5%
4 14
 
6.2%
5 14
 
6.2%
3 12
 
5.3%
9 11
 
4.9%
0 8
 
3.5%
6 8
 
3.5%
Other values (4) 11
 
4.9%
Hangul
ValueCountFrequency (%)
동 25
 
7.7%
인 24
 
7.4%
추 24
 
7.4%
구 24
 
7.4%
홀 24
 
7.4%
천 24
 
7.4%
미 24
 
7.4%
시 24
 
7.4%
역 24
 
7.4%
광 24
 
7.4%
Other values (26) 84
25.8%

도로명주소
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T07:03:00.727918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length24.5
Min length17

Characters and Unicode

Total characters588
Distinct characters76
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row인천광역시 미추홀구 인중로16번길 5-11
2nd row인천광역시 미추홀구 경인로 2 하나은행 3층
3rd row인천광역시 미추홀구 경원대로 869
4th row인천광역시 미추홀구 인주대로 468 형석빌딩401호
5th row인천광역시 미추홀구 소성로185번길 5 거성빌딩 5층
ValueCountFrequency (%)
인천광역시 24
20.0%
미추홀구 24
20.0%
경원대로 4
 
3.3%
869 4
 
3.3%
석정로 4
 
3.3%
경인로 3
 
2.5%
25 2
 
1.7%
5층 2
 
1.7%
소성로185번길 2
 
1.7%
3층 2
 
1.7%
Other values (47) 49
40.8%
2023-12-13T07:03:01.098441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
16.3%
인 30
 
5.1%
구 25
 
4.3%
광 24
 
4.1%
역 24
 
4.1%
시 24
 
4.1%
미 24
 
4.1%
추 24
 
4.1%
홀 24
 
4.1%
천 24
 
4.1%
Other values (66) 269
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 379
64.5%
Decimal Number 106
 
18.0%
Space Separator 96
 
16.3%
Dash Punctuation 5
 
0.9%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 30
 
7.9%
구 25
 
6.6%
광 24
 
6.3%
역 24
 
6.3%
시 24
 
6.3%
미 24
 
6.3%
추 24
 
6.3%
홀 24
 
6.3%
천 24
 
6.3%
로 24
 
6.3%
Other values (52) 132
34.8%
Decimal Number
ValueCountFrequency (%)
1 20
18.9%
5 15
14.2%
3 11
10.4%
8 11
10.4%
2 10
9.4%
6 9
8.5%
0 9
8.5%
9 8
 
7.5%
4 7
 
6.6%
7 6
 
5.7%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 379
64.5%
Common 209
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 30
 
7.9%
구 25
 
6.6%
광 24
 
6.3%
역 24
 
6.3%
시 24
 
6.3%
미 24
 
6.3%
추 24
 
6.3%
홀 24
 
6.3%
천 24
 
6.3%
로 24
 
6.3%
Other values (52) 132
34.8%
Common
ValueCountFrequency (%)
96
45.9%
1 20
 
9.6%
5 15
 
7.2%
3 11
 
5.3%
8 11
 
5.3%
2 10
 
4.8%
6 9
 
4.3%
0 9
 
4.3%
9 8
 
3.8%
4 7
 
3.3%
Other values (4) 13
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 379
64.5%
ASCII 209
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
45.9%
1 20
 
9.6%
5 15
 
7.2%
3 11
 
5.3%
8 11
 
5.3%
2 10
 
4.8%
6 9
 
4.3%
0 9
 
4.3%
9 8
 
3.8%
4 7
 
3.3%
Other values (4) 13
 
6.2%
Hangul
ValueCountFrequency (%)
인 30
 
7.9%
구 25
 
6.6%
광 24
 
6.3%
역 24
 
6.3%
시 24
 
6.3%
미 24
 
6.3%
추 24
 
6.3%
홀 24
 
6.3%
천 24
 
6.3%
로 24
 
6.3%
Other values (52) 132
34.8%

전화번호
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing2
Missing (%)8.3%
Memory size324.0 B
2023-12-13T07:03:01.337545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.090909
Min length12

Characters and Unicode

Total characters266
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

Unique22 ?
Unique (%)100.0%

Sample

1st row0507-1441-0193
2nd row032-420-1122
3rd row032-423-4000
4th row032-442-6878
5th row032-546-1063
ValueCountFrequency (%)
0507-1441-0193 1
 
4.5%
032-420-1122 1
 
4.5%
032-885-4230 1
 
4.5%
032-420-1600 1
 
4.5%
032-885-3868 1
 
4.5%
032-874-1406 1
 
4.5%
032-420-0144 1
 
4.5%
032-882-3495 1
 
4.5%
032-882-2642 1
 
4.5%
032-873-8318 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T07:03:01.703520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 44
16.5%
0 43
16.2%
2 39
14.7%
3 31
11.7%
8 28
10.5%
4 23
8.6%
1 19
7.1%
7 16
 
6.0%
6 11
 
4.1%
5 7
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 222
83.5%
Dash Punctuation 44
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
19.4%
2 39
17.6%
3 31
14.0%
8 28
12.6%
4 23
10.4%
1 19
8.6%
7 16
 
7.2%
6 11
 
5.0%
5 7
 
3.2%
9 5
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 266
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 44
16.5%
0 43
16.2%
2 39
14.7%
3 31
11.7%
8 28
10.5%
4 23
8.6%
1 19
7.1%
7 16
 
6.0%
6 11
 
4.1%
5 7
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 44
16.5%
0 43
16.2%
2 39
14.7%
3 31
11.7%
8 28
10.5%
4 23
8.6%
1 19
7.1%
7 16
 
6.0%
6 11
 
4.1%
5 7
 
2.6%

Interactions

2023-12-13T07:02:58.799594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:03:01.798076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0001.0000.9190.9191.000
상호명1.0001.0001.0001.0001.000
지번주소0.9191.0001.0001.0001.000
도로명주소0.9191.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-13T07:02:58.907537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:02:58.995489image/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

연번상호명지번주소도로명주소전화번호
01세무사신현배사무소인천광역시 미추홀구 숭의동 407-1인천광역시 미추홀구 인중로16번길 5-11<NA>
12하석용 김태웅 세무사 사무소인천광역시 미추홀구 숭의동 163-6 하나은행 3층인천광역시 미추홀구 경인로 2 하나은행 3층0507-1441-0193
23세무사최상동사무소인천광역시 미추홀구 주안동 989-1인천광역시 미추홀구 경원대로 869032-420-1122
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