Overview

Dataset statistics

Number of variables6
Number of observations341
Missing cells37
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Categorical1
Text3
DateTime1

Dataset

Description충청북도 제천시의 경로당에 관한 데이터로서 경로당 명칭을 비롯하여 도로명주소, 전화번호로 구성되어 있는 데이터입니다.
URLhttps://www.data.go.kr/data/15013784/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 연번High correlation
전화번호 has 37 (10.9%) missing valuesMissing
연번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:13:19.086700
Analysis finished2023-12-12 03:13:19.858992
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct341
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171
Minimum1
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T12:13:19.961106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q186
median171
Q3256
95-th percentile324
Maximum341
Range340
Interquartile range (IQR)170

Descriptive statistics

Standard deviation98.582453
Coefficient of variation (CV)0.57650557
Kurtosis-1.2
Mean171
Median Absolute Deviation (MAD)85
Skewness0
Sum58311
Variance9718.5
MonotonicityStrictly increasing
2023-12-12T12:13:20.131077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
226 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
Other values (331) 331
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%
335 1
0.3%
334 1
0.3%
333 1
0.3%
332 1
0.3%

읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
봉양읍
45 
송학면
26 
수산면
25 
백운면
25 
청풍면
23 
Other values (12)
197 

Length

Max length4
Median length3
Mean length2.9853372
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
봉양읍 45
13.2%
송학면 26
 
7.6%
수산면 25
 
7.3%
백운면 25
 
7.3%
청풍면 23
 
6.7%
신백동 23
 
6.7%
용두동 21
 
6.2%
교동 21
 
6.2%
화산동 20
 
5.9%
덕산면 20
 
5.9%
Other values (7) 92
27.0%

Length

2023-12-12T12:13:20.332401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
봉양읍 45
13.2%
송학면 26
 
7.6%
수산면 25
 
7.3%
백운면 25
 
7.3%
청풍면 23
 
6.7%
신백동 23
 
6.7%
용두동 21
 
6.2%
교동 21
 
6.2%
청전동 20
 
5.9%
화산동 20
 
5.9%
Other values (7) 92
27.0%

명칭
Text

Distinct339
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T12:13:20.632010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.8035191
Min length5

Characters and Unicode

Total characters2661
Distinct characters235
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

Unique337 ?
Unique (%)98.8%

Sample

1st row봉양읍 분회 경로당
2nd row주포리 경로당
3rd row주포리 중앙A 경로당
4th row원장평 경로당
5th row보래 경로당
ValueCountFrequency (%)
경로당 288
44.4%
연박리 3
 
0.5%
봉양리 3
 
0.5%
성내리 2
 
0.3%
구곡1리 2
 
0.3%
도기리 2
 
0.3%
주포리 2
 
0.3%
두진백로a 2
 
0.3%
장평리 2
 
0.3%
금용a 1
 
0.2%
Other values (341) 341
52.6%
2023-12-12T12:13:21.174101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 349
 
13.1%
당 349
 
13.1%
경 343
 
12.9%
319
 
12.0%
리 163
 
6.1%
2 40
 
1.5%
A 38
 
1.4%
1 35
 
1.3%
곡 30
 
1.1%
동 26
 
1.0%
Other values (225) 969
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2186
82.1%
Space Separator 319
 
12.0%
Decimal Number 94
 
3.5%
Uppercase Letter 41
 
1.5%
Open Punctuation 10
 
0.4%
Close Punctuation 10
 
0.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 349
16.0%
당 349
16.0%
경 343
15.7%
리 163
 
7.5%
곡 30
 
1.4%
동 26
 
1.2%
아 21
 
1.0%
산 21
 
1.0%
도 19
 
0.9%
지 19
 
0.9%
Other values (212) 846
38.7%
Decimal Number
ValueCountFrequency (%)
2 40
42.6%
1 35
37.2%
3 11
 
11.7%
4 7
 
7.4%
6 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
A 38
92.7%
L 1
 
2.4%
H 1
 
2.4%
E 1
 
2.4%
Space Separator
ValueCountFrequency (%)
319
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2186
82.1%
Common 434
 
16.3%
Latin 41
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 349
16.0%
당 349
16.0%
경 343
15.7%
리 163
 
7.5%
곡 30
 
1.4%
동 26
 
1.2%
아 21
 
1.0%
산 21
 
1.0%
도 19
 
0.9%
지 19
 
0.9%
Other values (212) 846
38.7%
Common
ValueCountFrequency (%)
319
73.5%
2 40
 
9.2%
1 35
 
8.1%
3 11
 
2.5%
( 10
 
2.3%
) 10
 
2.3%
4 7
 
1.6%
@ 1
 
0.2%
6 1
 
0.2%
Latin
ValueCountFrequency (%)
A 38
92.7%
L 1
 
2.4%
H 1
 
2.4%
E 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2186
82.1%
ASCII 475
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 349
16.0%
당 349
16.0%
경 343
15.7%
리 163
 
7.5%
곡 30
 
1.4%
동 26
 
1.2%
아 21
 
1.0%
산 21
 
1.0%
도 19
 
0.9%
지 19
 
0.9%
Other values (212) 846
38.7%
ASCII
ValueCountFrequency (%)
319
67.2%
2 40
 
8.4%
A 38
 
8.0%
1 35
 
7.4%
3 11
 
2.3%
( 10
 
2.1%
) 10
 
2.1%
4 7
 
1.5%
L 1
 
0.2%
H 1
 
0.2%
Other values (3) 3
 
0.6%

도로명주소
Text

UNIQUE 

Distinct341
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T12:13:21.556502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length22.847507
Min length15

Characters and Unicode

Total characters7791
Distinct characters179
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique341 ?
Unique (%)100.0%

Sample

1st row충청북도 제천시 봉양읍 주포로5길 8-5
2nd row충청북도 제천시 봉양읍 주포로5길 23
3rd row충청북도 제천시 봉양읍 주포리 225 중아아파트 804-509
4th row충청북도 제천시 봉양읍 제원로2길 69
5th row충청북도 제천시 봉양읍 앞산로 71
ValueCountFrequency (%)
제천시 342
21.5%
충청북도 341
21.5%
봉양읍 45
 
2.8%
송학면 26
 
1.6%
백운면 25
 
1.6%
수산면 25
 
1.6%
청풍면 23
 
1.4%
덕산면 20
 
1.3%
금성면 19
 
1.2%
한수면 8
 
0.5%
Other values (591) 715
45.0%
2023-12-12T12:13:22.138690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1248
 
16.0%
청 418
 
5.4%
천 381
 
4.9%
제 360
 
4.6%
도 354
 
4.5%
북 348
 
4.5%
시 346
 
4.4%
충 341
 
4.4%
로 305
 
3.9%
1 288
 
3.7%
Other values (169) 3402
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4972
63.8%
Space Separator 1248
 
16.0%
Decimal Number 1183
 
15.2%
Close Punctuation 147
 
1.9%
Open Punctuation 147
 
1.9%
Dash Punctuation 65
 
0.8%
Other Punctuation 27
 
0.3%
Uppercase Letter 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 418
 
8.4%
천 381
 
7.7%
제 360
 
7.2%
도 354
 
7.1%
북 348
 
7.0%
시 346
 
7.0%
충 341
 
6.9%
로 305
 
6.1%
길 246
 
4.9%
동 159
 
3.2%
Other values (151) 1714
34.5%
Decimal Number
ValueCountFrequency (%)
1 288
24.3%
2 183
15.5%
3 142
12.0%
4 103
 
8.7%
6 89
 
7.5%
0 88
 
7.4%
5 86
 
7.3%
7 79
 
6.7%
9 68
 
5.7%
8 57
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 24
88.9%
@ 3
 
11.1%
Space Separator
ValueCountFrequency (%)
1248
100.0%
Close Punctuation
ValueCountFrequency (%)
) 147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 147
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4972
63.8%
Common 2817
36.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 418
 
8.4%
천 381
 
7.7%
제 360
 
7.2%
도 354
 
7.1%
북 348
 
7.0%
시 346
 
7.0%
충 341
 
6.9%
로 305
 
6.1%
길 246
 
4.9%
동 159
 
3.2%
Other values (151) 1714
34.5%
Common
ValueCountFrequency (%)
1248
44.3%
1 288
 
10.2%
2 183
 
6.5%
) 147
 
5.2%
( 147
 
5.2%
3 142
 
5.0%
4 103
 
3.7%
6 89
 
3.2%
0 88
 
3.1%
5 86
 
3.1%
Other values (6) 296
 
10.5%
Latin
ValueCountFrequency (%)
A 1
50.0%
e 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4972
63.8%
ASCII 2819
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1248
44.3%
1 288
 
10.2%
2 183
 
6.5%
) 147
 
5.2%
( 147
 
5.2%
3 142
 
5.0%
4 103
 
3.7%
6 89
 
3.2%
0 88
 
3.1%
5 86
 
3.1%
Other values (8) 298
 
10.6%
Hangul
ValueCountFrequency (%)
청 418
 
8.4%
천 381
 
7.7%
제 360
 
7.2%
도 354
 
7.1%
북 348
 
7.0%
시 346
 
7.0%
충 341
 
6.9%
로 305
 
6.1%
길 246
 
4.9%
동 159
 
3.2%
Other values (151) 1714
34.5%

전화번호
Text

MISSING 

Distinct302
Distinct (%)99.3%
Missing37
Missing (%)10.9%
Memory size2.8 KiB
2023-12-12T12:13:22.454738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.967105
Min length1

Characters and Unicode

Total characters3638
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

Unique300 ?
Unique (%)98.7%

Sample

1st row043-651-4796
2nd row043-647-6021
3rd row043-647-9541
4th row043-647-4051
5th row043-646-2224
ValueCountFrequency (%)
043-646-8860 2
 
0.7%
043-651-7521 2
 
0.7%
043-647-1110 1
 
0.3%
043-642-2736 1
 
0.3%
043-651-4796 1
 
0.3%
043-652-0093 1
 
0.3%
043-642-7448 1
 
0.3%
043-648-1379 1
 
0.3%
043-647-0245 1
 
0.3%
043-646-7564 1
 
0.3%
Other values (292) 292
96.1%
2023-12-12T12:13:23.023108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 624
17.2%
- 607
16.7%
3 497
13.7%
0 459
12.6%
6 430
11.8%
5 255
7.0%
1 181
 
5.0%
2 170
 
4.7%
7 163
 
4.5%
8 134
 
3.7%
Other values (2) 118
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3030
83.3%
Dash Punctuation 607
 
16.7%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 624
20.6%
3 497
16.4%
0 459
15.1%
6 430
14.2%
5 255
8.4%
1 181
 
6.0%
2 170
 
5.6%
7 163
 
5.4%
8 134
 
4.4%
9 117
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 607
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3638
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 624
17.2%
- 607
16.7%
3 497
13.7%
0 459
12.6%
6 430
11.8%
5 255
7.0%
1 181
 
5.0%
2 170
 
4.7%
7 163
 
4.5%
8 134
 
3.7%
Other values (2) 118
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 624
17.2%
- 607
16.7%
3 497
13.7%
0 459
12.6%
6 430
11.8%
5 255
7.0%
1 181
 
5.0%
2 170
 
4.7%
7 163
 
4.5%
8 134
 
3.7%
Other values (2) 118
 
3.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2023-08-25 00:00:00
Maximum2023-08-25 00:00:00
2023-12-12T12:13:23.177859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:13:23.311266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T12:13:19.486392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:13:23.394329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동
연번1.0000.970
읍면동0.9701.000
2023-12-12T12:13:23.877594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동
연번1.0000.851
읍면동0.8511.000

Missing values

2023-12-12T12:13:19.650697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:13:19.793263image/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

연번읍면동명칭도로명주소전화번호데이터기준일자
01봉양읍봉양읍 분회 경로당충청북도 제천시 봉양읍 주포로5길 8-5043-651-47962023-08-25
12봉양읍주포리 경로당충청북도 제천시 봉양읍 주포로5길 23043-647-60212023-08-25
23봉양읍주포리 중앙A 경로당충청북도 제천시 봉양읍 주포리 225 중아아파트 804-509043-647-95412023-08-25
34봉양읍원장평 경로당충청북도 제천시 봉양읍 제원로2길 69043-647-40512023-08-25
45봉양읍보래 경로당충청북도 제천시 봉양읍 앞산로 71043-646-22242023-08-25
56봉양읍장평리 고산동 경로당충청북도 제천시 봉양읍 북부로10길 47043-647-76702023-08-25
67봉양읍장평리 고모동 경로당충청북도 제천시 봉양읍 고모동길 26<NA>2023-08-25
78봉양읍장평2리 구미 경로당충청북도 제천시 봉양읍 북부로11안길 31043-648-92292023-08-25
89봉양읍미당1리 경로당충청북도 제천시 봉양읍 용두대로34길 39<NA>2023-08-25
910봉양읍미당2리 경로당충청북도 제천시 봉양읍 용두대로36길 163-3043-646-06932023-08-25
연번읍면동명칭도로명주소전화번호데이터기준일자
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