Overview

Dataset statistics

Number of variables6
Number of observations269
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 KiB
Average record size in memory50.5 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description무주군 관내에 있는 경로당 현황 데이터로 경로당명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 데이터기준일자로 구성됨.
URLhttps://www.data.go.kr/data/15013940/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 16:14:33.901148
Analysis finished2023-12-12 16:14:34.793761
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct263
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T01:14:34.990577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.8364312
Min length5

Characters and Unicode

Total characters1570
Distinct characters143
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)95.9%

Sample

1st row가림경로당
2nd row가림할머니경로당
3rd row공정경로당
4th row교동경로당
5th row교동한빛할머니경로당
ValueCountFrequency (%)
신촌경로당 3
 
1.1%
교동할머니경로당 2
 
0.7%
내동경로당 2
 
0.7%
오동경로당 2
 
0.7%
교동경로당 2
 
0.7%
치목경로당 1
 
0.4%
중가경로당 1
 
0.4%
중리경로당 1
 
0.4%
중상가경로당 1
 
0.4%
하유할머니경로당 1
 
0.4%
Other values (253) 253
94.1%
2023-12-13T01:14:35.433604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
274
17.5%
269
17.1%
269
17.1%
58
 
3.7%
58
 
3.7%
58
 
3.7%
21
 
1.3%
20
 
1.3%
20
 
1.3%
20
 
1.3%
Other values (133) 503
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1570
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
274
17.5%
269
17.1%
269
17.1%
58
 
3.7%
58
 
3.7%
58
 
3.7%
21
 
1.3%
20
 
1.3%
20
 
1.3%
20
 
1.3%
Other values (133) 503
32.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1570
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
274
17.5%
269
17.1%
269
17.1%
58
 
3.7%
58
 
3.7%
58
 
3.7%
21
 
1.3%
20
 
1.3%
20
 
1.3%
20
 
1.3%
Other values (133) 503
32.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1570
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
274
17.5%
269
17.1%
269
17.1%
58
 
3.7%
58
 
3.7%
58
 
3.7%
21
 
1.3%
20
 
1.3%
20
 
1.3%
20
 
1.3%
Other values (133) 503
32.0%
Distinct228
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T01:14:35.830688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length20.234201
Min length18

Characters and Unicode

Total characters5443
Distinct characters156
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

Unique188 ?
Unique (%)69.9%

Sample

1st row전라북도 무주군 무주읍 가림동길 64
2nd row전라북도 무주군 무주읍 가림동길 64
3rd row전라북도 무주군 무주읍 공정길 7
4th row전라북도 무주군 무주읍 향학로 50
5th row전라북도 무주군 무주읍 교동길 21-11
ValueCountFrequency (%)
전라북도 269
20.0%
무주군 269
20.0%
무주읍 61
 
4.5%
안성면 58
 
4.3%
설천면 45
 
3.3%
적상면 43
 
3.2%
무풍면 39
 
2.9%
부남면 24
 
1.8%
9 9
 
0.7%
20 7
 
0.5%
Other values (339) 522
38.8%
2023-12-13T01:14:36.348483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1127
20.7%
375
 
6.9%
336
 
6.2%
282
 
5.2%
273
 
5.0%
273
 
5.0%
269
 
4.9%
269
 
4.9%
212
 
3.9%
209
 
3.8%
Other values (146) 1818
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3572
65.6%
Space Separator 1127
 
20.7%
Decimal Number 671
 
12.3%
Dash Punctuation 71
 
1.3%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
375
 
10.5%
336
 
9.4%
282
 
7.9%
273
 
7.6%
273
 
7.6%
269
 
7.5%
269
 
7.5%
212
 
5.9%
209
 
5.9%
69
 
1.9%
Other values (132) 1005
28.1%
Decimal Number
ValueCountFrequency (%)
1 176
26.2%
2 103
15.4%
3 96
14.3%
5 55
 
8.2%
4 54
 
8.0%
6 44
 
6.6%
7 36
 
5.4%
9 36
 
5.4%
8 36
 
5.4%
0 35
 
5.2%
Space Separator
ValueCountFrequency (%)
1127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3572
65.6%
Common 1871
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
375
 
10.5%
336
 
9.4%
282
 
7.9%
273
 
7.6%
273
 
7.6%
269
 
7.5%
269
 
7.5%
212
 
5.9%
209
 
5.9%
69
 
1.9%
Other values (132) 1005
28.1%
Common
ValueCountFrequency (%)
1127
60.2%
1 176
 
9.4%
2 103
 
5.5%
3 96
 
5.1%
- 71
 
3.8%
5 55
 
2.9%
4 54
 
2.9%
6 44
 
2.4%
7 36
 
1.9%
9 36
 
1.9%
Other values (4) 73
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3572
65.6%
ASCII 1871
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1127
60.2%
1 176
 
9.4%
2 103
 
5.5%
3 96
 
5.1%
- 71
 
3.8%
5 55
 
2.9%
4 54
 
2.9%
6 44
 
2.4%
7 36
 
1.9%
9 36
 
1.9%
Other values (4) 73
 
3.9%
Hangul
ValueCountFrequency (%)
375
 
10.5%
336
 
9.4%
282
 
7.9%
273
 
7.6%
273
 
7.6%
269
 
7.5%
269
 
7.5%
212
 
5.9%
209
 
5.9%
69
 
1.9%
Other values (132) 1005
28.1%
Distinct223
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T01:14:36.696518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length21.988848
Min length19

Characters and Unicode

Total characters5915
Distinct characters78
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

Unique179 ?
Unique (%)66.5%

Sample

1st row전라북도 무주군 무주읍 가옥리 216-1
2nd row전라북도 무주군 무주읍 가옥리 216-1
3rd row전라북도 무주군 무주읍 용포리 101-9
4th row전라북도 무주군 무주읍 읍내리 1402
5th row전라북도 무주군 무주읍 읍내리 283-2
ValueCountFrequency (%)
전라북도 269
20.0%
무주군 269
20.0%
무주읍 60
 
4.5%
안성면 58
 
4.3%
설천면 45
 
3.3%
적상면 43
 
3.2%
무풍면 39
 
2.9%
부남면 24
 
1.8%
읍내리 24
 
1.8%
금평리 12
 
0.9%
Other values (269) 503
37.4%
2023-12-13T01:14:37.172667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1078
18.2%
368
 
6.2%
329
 
5.6%
287
 
4.9%
1 283
 
4.8%
276
 
4.7%
271
 
4.6%
269
 
4.5%
269
 
4.5%
268
 
4.5%
Other values (68) 2217
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3499
59.2%
Decimal Number 1118
 
18.9%
Space Separator 1078
 
18.2%
Dash Punctuation 220
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
368
10.5%
329
 
9.4%
287
 
8.2%
276
 
7.9%
271
 
7.7%
269
 
7.7%
269
 
7.7%
268
 
7.7%
209
 
6.0%
84
 
2.4%
Other values (56) 869
24.8%
Decimal Number
ValueCountFrequency (%)
1 283
25.3%
3 112
 
10.0%
2 108
 
9.7%
4 107
 
9.6%
6 99
 
8.9%
7 97
 
8.7%
5 94
 
8.4%
8 78
 
7.0%
0 72
 
6.4%
9 68
 
6.1%
Space Separator
ValueCountFrequency (%)
1078
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3499
59.2%
Common 2416
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
368
10.5%
329
 
9.4%
287
 
8.2%
276
 
7.9%
271
 
7.7%
269
 
7.7%
269
 
7.7%
268
 
7.7%
209
 
6.0%
84
 
2.4%
Other values (56) 869
24.8%
Common
ValueCountFrequency (%)
1078
44.6%
1 283
 
11.7%
- 220
 
9.1%
3 112
 
4.6%
2 108
 
4.5%
4 107
 
4.4%
6 99
 
4.1%
7 97
 
4.0%
5 94
 
3.9%
8 78
 
3.2%
Other values (2) 140
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3499
59.2%
ASCII 2416
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1078
44.6%
1 283
 
11.7%
- 220
 
9.1%
3 112
 
4.6%
2 108
 
4.5%
4 107
 
4.4%
6 99
 
4.1%
7 97
 
4.0%
5 94
 
3.9%
8 78
 
3.2%
Other values (2) 140
 
5.8%
Hangul
ValueCountFrequency (%)
368
10.5%
329
 
9.4%
287
 
8.2%
276
 
7.9%
271
 
7.7%
269
 
7.7%
269
 
7.7%
268
 
7.7%
209
 
6.0%
84
 
2.4%
Other values (56) 869
24.8%

위도
Real number (ℝ)

Distinct214
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.946714
Minimum35.815256
Maximum36.055129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-13T01:14:37.306146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.815256
5-th percentile35.848098
Q135.903516
median35.958114
Q336.005432
95-th percentile36.025082
Maximum36.055129
Range0.239873
Interquartile range (IQR)0.101916

Descriptive statistics

Standard deviation0.060752311
Coefficient of variation (CV)0.0016900658
Kurtosis-0.98800113
Mean35.946714
Median Absolute Deviation (MAD)0.048386
Skewness-0.39867961
Sum9669.6661
Variance0.0036908432
MonotonicityNot monotonic
2023-12-13T01:14:37.434511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.965813 5
 
1.9%
35.815256 5
 
1.9%
36.006193 4
 
1.5%
35.885357 3
 
1.1%
35.967707 2
 
0.7%
36.009016 2
 
0.7%
35.872044 2
 
0.7%
35.962456 2
 
0.7%
35.970483 2
 
0.7%
35.873977 2
 
0.7%
Other values (204) 240
89.2%
ValueCountFrequency (%)
35.815256 5
1.9%
35.818537 1
 
0.4%
35.820245 1
 
0.4%
35.82903 2
 
0.7%
35.835035 2
 
0.7%
35.83958 1
 
0.4%
35.844672 1
 
0.4%
35.847711 1
 
0.4%
35.848678 2
 
0.7%
35.850634 2
 
0.7%
ValueCountFrequency (%)
36.055129 1
0.4%
36.048347 1
0.4%
36.047393 1
0.4%
36.045943 1
0.4%
36.033359 1
0.4%
36.033032 1
0.4%
36.031538 1
0.4%
36.029929 1
0.4%
36.029813 1
0.4%
36.028957 1
0.4%

경도
Real number (ℝ)

Distinct214
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.70005
Minimum127.54873
Maximum127.89862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-13T01:14:37.554598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.54873
5-th percentile127.57653
Q1127.6451
median127.67459
Q3127.77063
95-th percentile127.85199
Maximum127.89862
Range0.349888
Interquartile range (IQR)0.125526

Descriptive statistics

Standard deviation0.086654988
Coefficient of variation (CV)0.00067858224
Kurtosis-0.67740456
Mean127.70005
Median Absolute Deviation (MAD)0.046329
Skewness0.55773981
Sum34351.314
Variance0.0075090869
MonotonicityNot monotonic
2023-12-13T01:14:37.685647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.784824 5
 
1.9%
127.689586 5
 
1.9%
127.66041 4
 
1.5%
127.748688 3
 
1.1%
127.650576 2
 
0.7%
127.656616 2
 
0.7%
127.666118 2
 
0.7%
127.877569 2
 
0.7%
127.847069 2
 
0.7%
127.668235 2
 
0.7%
Other values (204) 240
89.2%
ValueCountFrequency (%)
127.548729 1
0.4%
127.551302 1
0.4%
127.552138 2
0.7%
127.555449 1
0.4%
127.558374 1
0.4%
127.561103 2
0.7%
127.567692 2
0.7%
127.572796 1
0.4%
127.573483 2
0.7%
127.575093 1
0.4%
ValueCountFrequency (%)
127.898617 1
0.4%
127.886715 1
0.4%
127.885355 1
0.4%
127.882347 1
0.4%
127.877569 2
0.7%
127.870118 1
0.4%
127.869505 1
0.4%
127.863475 1
0.4%
127.858252 1
0.4%
127.858138 1
0.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2023-03-07 00:00:00
Maximum2023-03-07 00:00:00
2023-12-13T01:14:37.804605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:14:38.190685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:14:34.386776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:14:34.190084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:14:34.504408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:14:34.285276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:14:38.264128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.700
경도0.7001.000
2023-12-13T01:14:38.353083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.049
경도0.0491.000

Missing values

2023-12-13T01:14:34.631058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:14:34.749126image/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

경로당명소재지도로명주소소재지지번주소위도경도데이터기준일자
0가림경로당전라북도 무주군 무주읍 가림동길 64전라북도 무주군 무주읍 가옥리 216-135.967707127.6505762023-03-07
1가림할머니경로당전라북도 무주군 무주읍 가림동길 64전라북도 무주군 무주읍 가옥리 216-135.967707127.6505762023-03-07
2공정경로당전라북도 무주군 무주읍 공정길 7전라북도 무주군 무주읍 용포리 101-935.985669127.6336292023-03-07
3교동경로당전라북도 무주군 무주읍 향학로 50전라북도 무주군 무주읍 읍내리 140236.008517127.6627672023-03-07
4교동한빛할머니경로당전라북도 무주군 무주읍 교동길 21-11전라북도 무주군 무주읍 읍내리 283-236.008983127.6644072023-03-07
5교동할머니경로당전라북도 무주군 무주읍 동산길 4전라북도 무주군 무주읍 읍내리 271-1136.007913127.6627122023-03-07
6굴천경로당전라북도 무주군 무주읍 굴천길 171전라북도 무주군 무주읍 내도리 904-336.048347127.6294342023-03-07
7남대천휴먼시아경로당전라북도 무주군 무주읍 장터로 26전라북도 무주군 무주읍 읍내리 1190-136.0065127.6533662023-03-07
8남천할머니경로당전라북도 무주군 무주읍 주계로 92-3전라북도 무주군 무주읍 읍내리 977-136.006193127.660412023-03-07
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