Overview

Dataset statistics

Number of variables10
Number of observations643
Missing cells106
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.6 KiB
Average record size in memory82.2 B

Variable types

Text4
Numeric2
Categorical4

Dataset

Description전북특별자치도 전주시 내의 경로당 현황을 제공하며 시설명, 전화번호, 도로명주소, 위경도 등을 제공합니다.항목 : 시설명, 전화번호, 도로명주소, 지번주소, 위도, 경도, 관할행정동, 관리기관 전화번호, 관리기관명자료: 통합돌봄과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15080574/fileData.do

Alerts

관리기관 전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 관할행정동High correlation
경도 is highly overall correlated with 관할행정동High correlation
관할행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
전화번호 has 82 (12.8%) missing valuesMissing
지번주소 has 8 (1.2%) missing valuesMissing
위도 has 8 (1.2%) missing valuesMissing
경도 has 8 (1.2%) missing valuesMissing

Reproduction

Analysis started2024-03-14 16:14:42.728230
Analysis finished2024-03-14 16:14:45.392168
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct618
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-15T01:14:46.102230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.1368585
Min length5

Characters and Unicode

Total characters4589
Distinct characters289
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

Unique597 ?
Unique (%)92.8%

Sample

1st row다가제일경로당
2nd row태평 2경로당
3rd row태평 1경로당
4th row연수정경로당
5th row일심자모경로당
ValueCountFrequency (%)
효성경로당 3
 
0.5%
중앙경로당 3
 
0.5%
영창경로당 3
 
0.5%
신일경로당 3
 
0.5%
비사벌경로당 2
 
0.3%
에코시티 2
 
0.3%
경로당 2
 
0.3%
태평 2
 
0.3%
신촌경로당 2
 
0.3%
삼우경로당 2
 
0.3%
Other values (615) 629
96.3%
2024-03-15T01:14:47.252808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 661
 
14.4%
경 649
 
14.1%
로 647
 
14.1%
아 92
 
2.0%
파 62
 
1.4%
성 62
 
1.4%
트 58
 
1.3%
신 55
 
1.2%
자 53
 
1.2%
동 49
 
1.1%
Other values (279) 2201
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4433
96.6%
Decimal Number 83
 
1.8%
Uppercase Letter 22
 
0.5%
Close Punctuation 17
 
0.4%
Open Punctuation 17
 
0.4%
Space Separator 10
 
0.2%
Dash Punctuation 3
 
0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 661
 
14.9%
경 649
 
14.6%
로 647
 
14.6%
아 92
 
2.1%
파 62
 
1.4%
성 62
 
1.4%
트 58
 
1.3%
신 55
 
1.2%
자 53
 
1.2%
동 49
 
1.1%
Other values (259) 2045
46.1%
Decimal Number
ValueCountFrequency (%)
2 32
38.6%
1 24
28.9%
3 12
 
14.5%
5 6
 
7.2%
6 4
 
4.8%
4 4
 
4.8%
7 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
A 10
45.5%
C 4
 
18.2%
K 3
 
13.6%
L 2
 
9.1%
H 2
 
9.1%
S 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
@ 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4433
96.6%
Common 132
 
2.9%
Latin 24
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 661
 
14.9%
경 649
 
14.6%
로 647
 
14.6%
아 92
 
2.1%
파 62
 
1.4%
성 62
 
1.4%
트 58
 
1.3%
신 55
 
1.2%
자 53
 
1.2%
동 49
 
1.1%
Other values (259) 2045
46.1%
Common
ValueCountFrequency (%)
2 32
24.2%
1 24
18.2%
) 17
12.9%
( 17
12.9%
3 12
 
9.1%
10
 
7.6%
5 6
 
4.5%
6 4
 
3.0%
4 4
 
3.0%
- 3
 
2.3%
Other values (3) 3
 
2.3%
Latin
ValueCountFrequency (%)
A 10
41.7%
C 4
 
16.7%
K 3
 
12.5%
L 2
 
8.3%
H 2
 
8.3%
e 2
 
8.3%
S 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4433
96.6%
ASCII 156
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 661
 
14.9%
경 649
 
14.6%
로 647
 
14.6%
아 92
 
2.1%
파 62
 
1.4%
성 62
 
1.4%
트 58
 
1.3%
신 55
 
1.2%
자 53
 
1.2%
동 49
 
1.1%
Other values (259) 2045
46.1%
ASCII
ValueCountFrequency (%)
2 32
20.5%
1 24
15.4%
) 17
10.9%
( 17
10.9%
3 12
 
7.7%
10
 
6.4%
A 10
 
6.4%
5 6
 
3.8%
6 4
 
2.6%
C 4
 
2.6%
Other values (10) 20
12.8%

전화번호
Text

MISSING 

Distinct554
Distinct (%)98.8%
Missing82
Missing (%)12.8%
Memory size5.1 KiB
2024-03-15T01:14:48.328887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length12
Mean length12.468806
Min length6

Characters and Unicode

Total characters6995
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique547 ?
Unique (%)97.5%

Sample

1st row063-284-7628
2nd row063-272-3691
3rd row063-275-6833
4th row063-284-5273
5th row063-284-2895
ValueCountFrequency (%)
063-211-8146 2
 
0.4%
063-211-7655 2
 
0.4%
063-223-7980 2
 
0.4%
063-902-0099 2
 
0.4%
063-255-4858 2
 
0.4%
063-274-1396 2
 
0.4%
063-284-6776 2
 
0.4%
063-901-3518 1
 
0.2%
063-254-7984 1
 
0.2%
063-274-6872 1
 
0.2%
Other values (546) 546
97.0%
2024-03-15T01:14:49.727757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1124
16.1%
2 946
13.5%
3 945
13.5%
0 902
12.9%
6 816
11.7%
5 386
 
5.5%
1 368
 
5.3%
4 360
 
5.1%
8 322
 
4.6%
7 322
 
4.6%
Other values (14) 504
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5620
80.3%
Dash Punctuation 1124
 
16.1%
Other Letter 174
 
2.5%
Open Punctuation 36
 
0.5%
Close Punctuation 36
 
0.5%
Space Separator 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 946
16.8%
3 945
16.8%
0 902
16.0%
6 816
14.5%
5 386
6.9%
1 368
 
6.5%
4 360
 
6.4%
8 322
 
5.7%
7 322
 
5.7%
9 253
 
4.5%
Other Letter
ValueCountFrequency (%)
무 34
19.5%
소 34
19.5%
관 34
19.5%
사 34
19.5%
리 34
19.5%
남 1
 
0.6%
여 1
 
0.6%
없 1
 
0.6%
음 1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 1124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6821
97.5%
Hangul 174
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1124
16.5%
2 946
13.9%
3 945
13.9%
0 902
13.2%
6 816
12.0%
5 386
 
5.7%
1 368
 
5.4%
4 360
 
5.3%
8 322
 
4.7%
7 322
 
4.7%
Other values (5) 330
 
4.8%
Hangul
ValueCountFrequency (%)
무 34
19.5%
소 34
19.5%
관 34
19.5%
사 34
19.5%
리 34
19.5%
남 1
 
0.6%
여 1
 
0.6%
없 1
 
0.6%
음 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6821
97.5%
Hangul 174
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1124
16.5%
2 946
13.9%
3 945
13.9%
0 902
13.2%
6 816
12.0%
5 386
 
5.7%
1 368
 
5.4%
4 360
 
5.3%
8 322
 
4.7%
7 322
 
4.7%
Other values (5) 330
 
4.8%
Hangul
ValueCountFrequency (%)
무 34
19.5%
소 34
19.5%
관 34
19.5%
사 34
19.5%
리 34
19.5%
남 1
 
0.6%
여 1
 
0.6%
없 1
 
0.6%
음 1
 
0.6%

도로명주소
Text

Distinct614
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-15T01:14:51.337284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length30
Mean length23.692068
Min length21

Characters and Unicode

Total characters15234
Distinct characters225
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique586 ?
Unique (%)91.1%

Sample

1st row전북특별자치도 전주시 완산구 전주천동로 200-50
2nd row전북특별자치도 전주시 완산구 물레방아1길 43-68
3rd row전북특별자치도 전주시 완산구 공북로 67-5
4th row전북특별자치도 전주시 완산구 전라감영5길 19-11
5th row전북특별자치도 전주시 완산구 전주객사2길 46-8
ValueCountFrequency (%)
전북특별자치도 643
20.0%
전주시 643
20.0%
덕진구 328
 
10.2%
완산구 315
 
9.8%
11 16
 
0.5%
8 15
 
0.5%
10 14
 
0.4%
16 12
 
0.4%
22 12
 
0.4%
40 11
 
0.3%
Other values (710) 1207
37.5%
2024-03-15T01:14:53.349127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2574
16.9%
전 1310
 
8.6%
주 656
 
4.3%
구 654
 
4.3%
북 652
 
4.3%
도 647
 
4.2%
자 645
 
4.2%
치 644
 
4.2%
시 644
 
4.2%
특 643
 
4.2%
Other values (215) 6165
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10636
69.8%
Space Separator 2574
 
16.9%
Decimal Number 1856
 
12.2%
Dash Punctuation 161
 
1.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1310
 
12.3%
주 656
 
6.2%
구 654
 
6.1%
북 652
 
6.1%
도 647
 
6.1%
자 645
 
6.1%
치 644
 
6.1%
시 644
 
6.1%
특 643
 
6.0%
별 643
 
6.0%
Other values (200) 3498
32.9%
Decimal Number
ValueCountFrequency (%)
1 423
22.8%
2 269
14.5%
3 225
12.1%
4 177
9.5%
5 170
9.2%
6 137
 
7.4%
0 124
 
6.7%
7 121
 
6.5%
8 113
 
6.1%
9 97
 
5.2%
Space Separator
ValueCountFrequency (%)
2574
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10636
69.8%
Common 4598
30.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1310
 
12.3%
주 656
 
6.2%
구 654
 
6.1%
북 652
 
6.1%
도 647
 
6.1%
자 645
 
6.1%
치 644
 
6.1%
시 644
 
6.1%
특 643
 
6.0%
별 643
 
6.0%
Other values (200) 3498
32.9%
Common
ValueCountFrequency (%)
2574
56.0%
1 423
 
9.2%
2 269
 
5.9%
3 225
 
4.9%
4 177
 
3.8%
5 170
 
3.7%
- 161
 
3.5%
6 137
 
3.0%
0 124
 
2.7%
7 121
 
2.6%
Other values (5) 217
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10636
69.8%
ASCII 4598
30.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2574
56.0%
1 423
 
9.2%
2 269
 
5.9%
3 225
 
4.9%
4 177
 
3.8%
5 170
 
3.7%
- 161
 
3.5%
6 137
 
3.0%
0 124
 
2.7%
7 121
 
2.6%
Other values (5) 217
 
4.7%
Hangul
ValueCountFrequency (%)
전 1310
 
12.3%
주 656
 
6.2%
구 654
 
6.1%
북 652
 
6.1%
도 647
 
6.1%
자 645
 
6.1%
치 644
 
6.1%
시 644
 
6.1%
특 643
 
6.0%
별 643
 
6.0%
Other values (200) 3498
32.9%

지번주소
Text

MISSING 

Distinct603
Distinct (%)95.0%
Missing8
Missing (%)1.2%
Memory size5.1 KiB
2024-03-15T01:14:55.733927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length26.119685
Min length22

Characters and Unicode

Total characters16586
Distinct characters76
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

Unique572 ?
Unique (%)90.1%

Sample

1st row전북특별자치도 전주시 완산구 다가동2가 113-1
2nd row전북특별자치도 전주시 완산구 태평동 153-4
3rd row전북특별자치도 전주시 완산구 태평동 13-18
4th row전북특별자치도 전주시 완산구 중앙동3가 31-3
5th row전북특별자치도 전주시 완산구 고사동 480-3
ValueCountFrequency (%)
전북특별자치도 635
20.0%
전주시 635
20.0%
덕진구 323
 
10.2%
완산구 312
 
9.8%
효자동1가 43
 
1.4%
인후동1가 36
 
1.1%
삼천동1가 32
 
1.0%
송천동1가 32
 
1.0%
송천동2가 28
 
0.9%
서신동 25
 
0.8%
Other values (654) 1079
33.9%
2024-03-15T01:14:58.211515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2545
 
15.3%
전 1283
 
7.7%
자 712
 
4.3%
1 686
 
4.1%
북 655
 
3.9%
동 649
 
3.9%
도 639
 
3.9%
구 638
 
3.8%
특 635
 
3.8%
별 635
 
3.8%
Other values (66) 7509
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10627
64.1%
Decimal Number 2944
 
17.7%
Space Separator 2545
 
15.3%
Dash Punctuation 470
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1283
 
12.1%
자 712
 
6.7%
북 655
 
6.2%
동 649
 
6.1%
도 639
 
6.0%
구 638
 
6.0%
특 635
 
6.0%
별 635
 
6.0%
치 635
 
6.0%
주 635
 
6.0%
Other values (54) 3511
33.0%
Decimal Number
ValueCountFrequency (%)
1 686
23.3%
2 438
14.9%
3 327
11.1%
5 275
9.3%
4 246
 
8.4%
7 235
 
8.0%
6 206
 
7.0%
9 186
 
6.3%
8 180
 
6.1%
0 165
 
5.6%
Space Separator
ValueCountFrequency (%)
2545
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 470
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10627
64.1%
Common 5959
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1283
 
12.1%
자 712
 
6.7%
북 655
 
6.2%
동 649
 
6.1%
도 639
 
6.0%
구 638
 
6.0%
특 635
 
6.0%
별 635
 
6.0%
치 635
 
6.0%
주 635
 
6.0%
Other values (54) 3511
33.0%
Common
ValueCountFrequency (%)
2545
42.7%
1 686
 
11.5%
- 470
 
7.9%
2 438
 
7.4%
3 327
 
5.5%
5 275
 
4.6%
4 246
 
4.1%
7 235
 
3.9%
6 206
 
3.5%
9 186
 
3.1%
Other values (2) 345
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10627
64.1%
ASCII 5959
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2545
42.7%
1 686
 
11.5%
- 470
 
7.9%
2 438
 
7.4%
3 327
 
5.5%
5 275
 
4.6%
4 246
 
4.1%
7 235
 
3.9%
6 206
 
3.5%
9 186
 
3.1%
Other values (2) 345
 
5.8%
Hangul
ValueCountFrequency (%)
전 1283
 
12.1%
자 712
 
6.7%
북 655
 
6.2%
동 649
 
6.1%
도 639
 
6.0%
구 638
 
6.0%
특 635
 
6.0%
별 635
 
6.0%
치 635
 
6.0%
주 635
 
6.0%
Other values (54) 3511
33.0%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct607
Distinct (%)95.6%
Missing8
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean35.830699
Minimum35.755024
Maximum35.89822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-03-15T01:14:58.841319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.755024
5-th percentile35.78784
Q135.806878
median35.830879
Q335.854912
95-th percentile35.877725
Maximum35.89822
Range0.14319569
Interquartile range (IQR)0.04803429

Descriptive statistics

Standard deviation0.029360173
Coefficient of variation (CV)0.00081941392
Kurtosis-0.69062568
Mean35.830699
Median Absolute Deviation (MAD)0.02400927
Skewness0.080629834
Sum22752.494
Variance0.00086201978
MonotonicityNot monotonic
2024-03-15T01:14:59.208053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.82983141 3
 
0.5%
35.84226333 2
 
0.3%
35.86692549 2
 
0.3%
35.83326281 2
 
0.3%
35.82054637 2
 
0.3%
35.8304231 2
 
0.3%
35.82398563 2
 
0.3%
35.83184978 2
 
0.3%
35.82791173 2
 
0.3%
35.85823574 2
 
0.3%
Other values (597) 614
95.5%
(Missing) 8
 
1.2%
ValueCountFrequency (%)
35.75502444 1
0.2%
35.75989256 1
0.2%
35.76096566 1
0.2%
35.76295372 1
0.2%
35.76366336 1
0.2%
35.76454089 1
0.2%
35.76457039 1
0.2%
35.76492285 1
0.2%
35.76526068 1
0.2%
35.76690885 1
0.2%
ValueCountFrequency (%)
35.89822013 1
0.2%
35.89793012 1
0.2%
35.89603506 1
0.2%
35.89428291 1
0.2%
35.89240455 1
0.2%
35.89238641 1
0.2%
35.89226164 1
0.2%
35.89165507 1
0.2%
35.89127998 1
0.2%
35.890276 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct607
Distinct (%)95.6%
Missing8
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean127.12304
Minimum127.00214
Maximum127.20184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-03-15T01:14:59.479717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.00214
5-th percentile127.06232
Q1127.11104
median127.12658
Q3127.14506
95-th percentile127.16537
Maximum127.20184
Range0.1996989
Interquartile range (IQR)0.034019

Descriptive statistics

Standard deviation0.031914783
Coefficient of variation (CV)0.00025105428
Kurtosis1.2100737
Mean127.12304
Median Absolute Deviation (MAD)0.0170132
Skewness-0.7755133
Sum80723.129
Variance0.0010185534
MonotonicityNot monotonic
2024-03-15T01:14:59.767564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1546343 3
 
0.5%
127.0967518 2
 
0.3%
127.1000146 2
 
0.3%
127.1291828 2
 
0.3%
127.133991 2
 
0.3%
127.1355041 2
 
0.3%
127.131083 2
 
0.3%
127.1367929 2
 
0.3%
127.132693 2
 
0.3%
127.0346046 2
 
0.3%
Other values (597) 614
95.5%
(Missing) 8
 
1.2%
ValueCountFrequency (%)
127.0021412 1
0.2%
127.0158111 1
0.2%
127.0175816 1
0.2%
127.0176331 1
0.2%
127.0177096 1
0.2%
127.0180721 1
0.2%
127.0246902 1
0.2%
127.0252158 1
0.2%
127.0274476 1
0.2%
127.0315637 2
0.3%
ValueCountFrequency (%)
127.2018401 1
0.2%
127.1997695 1
0.2%
127.1986902 1
0.2%
127.1969535 1
0.2%
127.1967703 1
0.2%
127.1940025 1
0.2%
127.1931449 1
0.2%
127.1924084 1
0.2%
127.1905638 1
0.2%
127.1898376 1
0.2%

관할행정동
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
송천1동
 
37
조촌동
 
35
평화2동
 
33
송천2동
 
32
여의동
 
31
Other values (30)
475 

Length

Max length5
Median length4
Mean length3.6625194
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
송천1동 37
 
5.8%
조촌동 35
 
5.4%
평화2동 33
 
5.1%
송천2동 32
 
5.0%
여의동 31
 
4.8%
삼천3동 31
 
4.8%
서신동 26
 
4.0%
덕진동 25
 
3.9%
호성동 25
 
3.9%
효자4동 22
 
3.4%
Other values (25) 346
53.8%

Length

2024-03-15T01:15:00.256470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송천1동 37
 
5.8%
조촌동 35
 
5.4%
평화2동 33
 
5.1%
송천2동 32
 
5.0%
여의동 31
 
4.8%
삼천3동 31
 
4.8%
서신동 26
 
4.0%
호성동 25
 
3.9%
덕진동 25
 
3.9%
효자4동 22
 
3.4%
Other values (25) 346
53.8%

관리기관 전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
063-281-2318
643 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row063-281-2318
2nd row063-281-2318
3rd row063-281-2318
4th row063-281-2318
5th row063-281-2318

Common Values

ValueCountFrequency (%)
063-281-2318 643
100.0%

Length

2024-03-15T01:15:00.488691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:15:00.656674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
063-281-2318 643
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
전북특별자치도 전주시청
643 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 전주시청
2nd row전북특별자치도 전주시청
3rd row전북특별자치도 전주시청
4th row전북특별자치도 전주시청
5th row전북특별자치도 전주시청

Common Values

ValueCountFrequency (%)
전북특별자치도 전주시청 643
100.0%

Length

2024-03-15T01:15:00.921563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:15:01.235178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 643
50.0%
전주시청 643
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-11-28
643 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-28
2nd row2023-11-28
3rd row2023-11-28
4th row2023-11-28
5th row2023-11-28

Common Values

ValueCountFrequency (%)
2023-11-28 643
100.0%

Length

2024-03-15T01:15:01.691174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:15:02.036245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-28 643
100.0%

Interactions

2024-03-15T01:14:44.078738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:14:43.508414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:14:44.364196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:14:43.788175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:15:02.214709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도관할행정동
위도1.0000.6200.920
경도0.6201.0000.915
관할행정동0.9200.9151.000
2024-03-15T01:15:02.459139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도관할행정동
위도1.000-0.1920.618
경도-0.1921.0000.607
관할행정동0.6180.6071.000

Missing values

2024-03-15T01:14:44.727184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:14:44.992050image/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.
2024-03-15T01:14:45.232745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시설명전화번호도로명주소지번주소위도경도관할행정동관리기관 전화번호관리기관명데이터기준일자
0다가제일경로당063-284-7628전북특별자치도 전주시 완산구 전주천동로 200-50전북특별자치도 전주시 완산구 다가동2가 113-135.814489127.140364중앙동063-281-2318전북특별자치도 전주시청2023-11-28
1태평 2경로당063-272-3691전북특별자치도 전주시 완산구 물레방아1길 43-68전북특별자치도 전주시 완산구 태평동 153-435.822139127.136319중앙동063-281-2318전북특별자치도 전주시청2023-11-28
2태평 1경로당063-275-6833전북특별자치도 전주시 완산구 공북로 67-5전북특별자치도 전주시 완산구 태평동 13-1835.826224127.138975중앙동063-281-2318전북특별자치도 전주시청2023-11-28
3연수정경로당063-284-5273전북특별자치도 전주시 완산구 전라감영5길 19-11전북특별자치도 전주시 완산구 중앙동3가 31-335.81735127.145163중앙동063-281-2318전북특별자치도 전주시청2023-11-28
4일심자모경로당063-284-2895전북특별자치도 전주시 완산구 전주객사2길 46-8전북특별자치도 전주시 완산구 고사동 480-335.818842127.140979중앙동063-281-2318전북특별자치도 전주시청2023-11-28
5만수제경로당063-275-4395전북특별자치도 전주시 완산구 공북1길 11전북특별자치도 전주시 완산구 태평동 253-535.826531127.137301중앙동063-281-2318전북특별자치도 전주시청2023-11-28
6태평자모경로당063-271-3007전북특별자치도 전주시 완산구 물레방아1길 43-68전북특별자치도 전주시 완산구 태평동 153-435.822139127.136319중앙동063-281-2318전북특별자치도 전주시청2023-11-28
7중앙아파트경로당063-275-7248(관리사무소)전북특별자치도 전주시 완산구 태평3길 70전북특별자치도 전주시 완산구 태평동 9-335.825226127.142458중앙동063-281-2318전북특별자치도 전주시청2023-11-28
8중앙경로당063-288-3123전북특별자치도 전주시 완산구 전라감영2길 12-9전북특별자치도 전주시 완산구 중앙동1가 66-335.815532127.142342중앙동063-281-2318전북특별자치도 전주시청2023-11-28
9SK뷰아파트경로당063-252-0132전북특별자치도 전주시 완산구 태평2길 22전북특별자치도 전주시 완산구 태평동 29135.824741127.140032중앙동063-281-2318전북특별자치도 전주시청2023-11-28
시설명전화번호도로명주소지번주소위도경도관할행정동관리기관 전화번호관리기관명데이터기준일자
633호성주공2단지경로당063-245-0353전북특별자치도 전주시 덕진구 소리로 179전북특별자치도 전주시 덕진구 호성동1가 90035.858039127.150075호성동063-281-2318전북특별자치도 전주시청2023-11-28
634화정경로당063-253-1242전북특별자치도 전주시 덕진구 화정길 60전북특별자치도 전주시 덕진구 호성동2가 731-135.873722127.143596호성동063-281-2318전북특별자치도 전주시청2023-11-28
635엘에이치이노팰리스경로당063-212-9972(관리사무소)전북특별자치도 전주시 덕진구 틀못4길 33전북특별자치도 전주시 덕진구 장동 108235.845713127.058911혁신동063-281-2318전북특별자치도 전주시청2023-11-28
636우미린2단지경로당063-904-2062전북특별자치도 전주시 덕진구 틀못4길 17전북특별자치도 전주시 덕진구 장동 106335.843969127.057322혁신동063-281-2318전북특별자치도 전주시청2023-11-28
637전북혁신베르디움1차경로당063-225-8755(관리사무소)전북특별자치도 전주시 덕진구 오공로 71전북특별자치도 전주시 덕진구 중동 78935.838056127.062305혁신동063-281-2318전북특별자치도 전주시청2023-11-28
638전북혁신베르디움3차경로당063-237-5166(관리사무소)전북특별자치도 전주시 덕진구 오공로 100전북특별자치도 전주시 덕진구 중동 80735.835515127.066309혁신동063-281-2318전북특별자치도 전주시청2023-11-28
639전북혁신우미린1단지경로당063-236-1680전북특별자치도 전주시 덕진구 오공로 70전북특별자치도 전주시 덕진구 중동 79835.835446127.062321혁신동063-281-2318전북특별자치도 전주시청2023-11-28
640혁신중흥에스클래스경로당<NA>전북특별자치도 전주시 덕진구 틀못3길 16전북특별자치도 전주시 덕진구 장동 106435.841781127.055538혁신동063-281-2318전북특별자치도 전주시청2023-11-28
641호반베르디움더클래스경로당063-211-0730전북특별자치도 전주시 덕진구 출판로 87전북특별자치도 전주시 덕진구 장동 108635.839875127.062404혁신동063-281-2318전북특별자치도 전주시청2023-11-28
642호반센트럴2경로당063-213-9903(관리사무소)전북특별자치도 전주시 덕진구 출판로 69전북특별자치도 전주시 덕진구 장동 107535.839933127.061098혁신동063-281-2318전북특별자치도 전주시청2023-11-28