Overview

Dataset statistics

Number of variables9
Number of observations6680
Missing cells600
Missing cells (%)1.0%
Duplicate rows187
Duplicate rows (%)2.8%
Total size in memory469.8 KiB
Average record size in memory72.0 B

Variable types

Unsupported4
Categorical4
Text1

Alerts

Dataset has 187 (2.8%) duplicate rowsDuplicates
Unnamed: 1 is highly overall correlated with Unnamed: 2 and 2 other fieldsHigh correlation
Unnamed: 2 is highly overall correlated with Unnamed: 1 and 1 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 6 is highly overall correlated with Unnamed: 1 and 1 other fieldsHigh correlation
Unnamed: 1 is highly imbalanced (99.6%)Imbalance
Unnamed: 5 is highly imbalanced (71.2%)Imbalance
Unnamed: 6 is highly imbalanced (77.4%)Imbalance
Unnamed: 8 has 596 (8.9%) missing valuesMissing
경로당현황(2019년) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:59:55.803400
Analysis finished2024-03-14 02:59:56.727986
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

경로당현황(2019년)
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size52.3 KiB

Unnamed: 1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.3 KiB
전라북도
6676 
<NA>
 
1
소재지 시도
 
1
전라북도
 
1
전라북도
 
1

Length

Max length6
Median length4
Mean length4.0007485
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row소재지 시도
3rd row전라북도
4th row전라북도
5th row전라북도

Common Values

ValueCountFrequency (%)
전라북도 6676
99.9%
<NA> 1
 
< 0.1%
소재지 시도 1
 
< 0.1%
전라북도 1
 
< 0.1%
전라북도 1
 
< 0.1%

Length

2024-03-14T11:59:56.790864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:59:56.876503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 6678
> 99.9%
na 1
 
< 0.1%
소재지 1
 
< 0.1%
시도 1
 
< 0.1%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.3 KiB
정읍시
692 
익산시
669 
김제시
622 
고창군
589 
군산시
503 
Other values (15)
3605 

Length

Max length7
Median length3
Mean length3.3679641
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row소재지 시군구
3rd row전주시 완산구
4th row전주시 완산구
5th row전주시 완산구

Common Values

ValueCountFrequency (%)
정읍시 692
10.4%
익산시 669
10.0%
김제시 622
9.3%
고창군 589
 
8.8%
군산시 503
 
7.5%
남원시 487
 
7.3%
부안군 472
 
7.1%
완주군 437
 
6.5%
순창군 371
 
5.6%
임실군 343
 
5.1%
Other values (10) 1495
22.4%

Length

2024-03-14T11:59:56.973230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정읍시 694
 
9.5%
익산시 675
 
9.3%
김제시 622
 
8.5%
전주시 610
 
8.4%
고창군 589
 
8.1%
군산시 508
 
7.0%
남원시 487
 
6.7%
부안군 472
 
6.5%
완주군 437
 
6.0%
순창군 371
 
5.1%
Other values (9) 1826
25.0%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size52.3 KiB

Unnamed: 4
Text

Distinct6486
Distinct (%)97.1%
Missing1
Missing (%)< 0.1%
Memory size52.3 KiB
2024-03-14T11:59:57.265460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length17.094924
Min length5

Characters and Unicode

Total characters114177
Distinct characters500
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6295 ?
Unique (%)94.3%

Sample

1st row소재지도로명주소
2nd row전라북도 전주시 완산구 전주천동로 200-50(다가동2가)
3rd row전라북도 전주시 완산구 물레방아1길 43-68(태평동)
4th row전라북도 전주시 완산구 공북로67-5(태평동)
5th row전라북도 전주시 완산구 전라감영5길 19-11(중앙동3가)
ValueCountFrequency (%)
전라북도 3133
 
11.5%
익산시 664
 
2.4%
전주시 610
 
2.2%
정읍시 499
 
1.8%
부안군 472
 
1.7%
군산시 452
 
1.7%
완주군 437
 
1.6%
전북 406
 
1.5%
순창군 371
 
1.4%
임실군 370
 
1.4%
Other values (7332) 19741
72.7%
2024-03-14T11:59:57.759750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21016
 
18.4%
길 5318
 
4.7%
1 4743
 
4.2%
면 4461
 
3.9%
전 4320
 
3.8%
북 3690
 
3.2%
도 3273
 
2.9%
라 3193
 
2.8%
2 3106
 
2.7%
산 2856
 
2.5%
Other values (490) 58201
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70087
61.4%
Space Separator 21172
 
18.5%
Decimal Number 19354
 
17.0%
Dash Punctuation 2216
 
1.9%
Close Punctuation 510
 
0.4%
Open Punctuation 510
 
0.4%
Other Punctuation 285
 
0.2%
Uppercase Letter 35
 
< 0.1%
Control 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 5318
 
7.6%
면 4461
 
6.4%
전 4320
 
6.2%
북 3690
 
5.3%
도 3273
 
4.7%
라 3193
 
4.6%
산 2856
 
4.1%
군 2726
 
3.9%
시 2307
 
3.3%
동 1493
 
2.1%
Other values (460) 36450
52.0%
Decimal Number
ValueCountFrequency (%)
1 4743
24.5%
2 3106
16.0%
3 2330
12.0%
4 1788
 
9.2%
5 1566
 
8.1%
6 1375
 
7.1%
7 1183
 
6.1%
8 1114
 
5.8%
9 1086
 
5.6%
0 1063
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 23
65.7%
B 2
 
5.7%
L 2
 
5.7%
H 2
 
5.7%
S 1
 
2.9%
K 1
 
2.9%
V 1
 
2.9%
I 1
 
2.9%
E 1
 
2.9%
W 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 254
89.1%
@ 20
 
7.0%
/ 9
 
3.2%
. 2
 
0.7%
Space Separator
ValueCountFrequency (%)
21016
99.3%
  156
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 2216
100.0%
Close Punctuation
ValueCountFrequency (%)
) 510
100.0%
Open Punctuation
ValueCountFrequency (%)
( 510
100.0%
Control
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70087
61.4%
Common 44055
38.6%
Latin 35
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 5318
 
7.6%
면 4461
 
6.4%
전 4320
 
6.2%
북 3690
 
5.3%
도 3273
 
4.7%
라 3193
 
4.6%
산 2856
 
4.1%
군 2726
 
3.9%
시 2307
 
3.3%
동 1493
 
2.1%
Other values (460) 36450
52.0%
Common
ValueCountFrequency (%)
21016
47.7%
1 4743
 
10.8%
2 3106
 
7.1%
3 2330
 
5.3%
- 2216
 
5.0%
4 1788
 
4.1%
5 1566
 
3.6%
6 1375
 
3.1%
7 1183
 
2.7%
8 1114
 
2.5%
Other values (10) 3618
 
8.2%
Latin
ValueCountFrequency (%)
A 23
65.7%
B 2
 
5.7%
L 2
 
5.7%
H 2
 
5.7%
S 1
 
2.9%
K 1
 
2.9%
V 1
 
2.9%
I 1
 
2.9%
E 1
 
2.9%
W 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70087
61.4%
ASCII 43934
38.5%
None 156
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21016
47.8%
1 4743
 
10.8%
2 3106
 
7.1%
3 2330
 
5.3%
- 2216
 
5.0%
4 1788
 
4.1%
5 1566
 
3.6%
6 1375
 
3.1%
7 1183
 
2.7%
8 1114
 
2.5%
Other values (19) 3497
 
8.0%
Hangul
ValueCountFrequency (%)
길 5318
 
7.6%
면 4461
 
6.4%
전 4320
 
6.2%
북 3690
 
5.3%
도 3273
 
4.7%
라 3193
 
4.6%
산 2856
 
4.1%
군 2726
 
3.9%
시 2307
 
3.3%
동 1493
 
2.1%
Other values (460) 36450
52.0%
None
ValueCountFrequency (%)
  156
100.0%

Unnamed: 5
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.3 KiB
단독
5070 
아파트
719 
마을회관
680 
복지회관
 
178
경로당
 
14
Other values (12)
 
19

Length

Max length14
Median length2
Mean length2.3715569
Min length2

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row시설구분
3rd row단독
4th row단독
5th row단독

Common Values

ValueCountFrequency (%)
단독 5070
75.9%
아파트 719
 
10.8%
마을회관 680
 
10.2%
복지회관 178
 
2.7%
경로당 14
 
0.2%
단독 3
 
< 0.1%
시립 3
 
< 0.1%
연립 3
 
< 0.1%
회관 2
 
< 0.1%
노인복지회관 1
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2024-03-14T11:59:57.884025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독 5074
75.9%
아파트 719
 
10.8%
마을회관 680
 
10.2%
복지회관 178
 
2.7%
경로당 15
 
0.2%
시립 3
 
< 0.1%
연립 3
 
< 0.1%
회관 2
 
< 0.1%
시설구분 1
 
< 0.1%
단독건물 1
 
< 0.1%
Other values (7) 7
 
0.1%

Unnamed: 6
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.3 KiB
민영
5658 
민간
892 
공공
 
116
아파트
 
7
군산시
 
3
Other values (4)
 
4

Length

Max length4
Median length2
Mean length2.0022455
Min length2

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row운영주체
3rd row민영
4th row민영
5th row민영

Common Values

ValueCountFrequency (%)
민영 5658
84.7%
민간 892
 
13.4%
공공 116
 
1.7%
아파트 7
 
0.1%
군산시 3
 
< 0.1%
<NA> 1
 
< 0.1%
운영주체 1
 
< 0.1%
단독 1
 
< 0.1%
지자체 1
 
< 0.1%

Length

2024-03-14T11:59:58.015461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:59:58.109287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민영 5658
84.7%
민간 892
 
13.4%
공공 116
 
1.7%
아파트 7
 
0.1%
군산시 3
 
< 0.1%
na 1
 
< 0.1%
운영주체 1
 
< 0.1%
단독 1
 
< 0.1%
지자체 1
 
< 0.1%

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size52.3 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)8.9%
Memory size52.3 KiB

Correlations

2024-03-14T11:59:58.178553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 5Unnamed: 6
Unnamed: 11.0000.7960.8600.886
Unnamed: 20.7961.0000.7870.837
Unnamed: 50.8600.7871.0000.776
Unnamed: 60.8860.8370.7761.000
2024-03-14T11:59:58.271817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 5Unnamed: 6Unnamed: 2Unnamed: 1
Unnamed: 51.0000.3900.3820.576
Unnamed: 60.3901.0000.5520.577
Unnamed: 20.3820.5521.0000.576
Unnamed: 10.5760.5770.5761.000
2024-03-14T11:59:58.356823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 5Unnamed: 6
Unnamed: 11.0000.5760.5760.577
Unnamed: 20.5761.0000.3820.552
Unnamed: 50.5760.3821.0000.390
Unnamed: 60.5770.5520.3901.000

Missing values

2024-03-14T11:59:56.336374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:59:56.505183image/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.
2024-03-14T11:59:56.641591image/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

경로당현황(2019년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0NaN<NA><NA>NaN<NA><NA><NA>NaNNaN
1연번소재지 시도소재지 시군구경로당명소재지도로명주소시설구분운영주체정원(수용능력)설립년도
21전라북도전주시 완산구다가제일경로당전라북도 전주시 완산구 전주천동로 200-50(다가동2가)단독민영371989
32전라북도전주시 완산구태평 2경로당전라북도 전주시 완산구 물레방아1길 43-68(태평동)단독민영261989
43전라북도전주시 완산구태평 1경로당전라북도 전주시 완산구 공북로67-5(태평동)단독민영431989
54전라북도전주시 완산구연수정경로당전라북도 전주시 완산구 전라감영5길 19-11(중앙동3가)단독민영211989
65전라북도전주시 완산구일심자모경로당전라북도 전주시 완산구 전주객사2길 46-8(고사동)단독민영371989
76전라북도전주시 완산구만수제경로당전라북도 전주시 완산구 공북1길 11(태평동)단독민영621993
87전라북도전주시 완산구태평자모경로당전라북도 전주시 완산구 물레방아1길 43-68(태평동)단독민영381999
98전라북도전주시 완산구중앙아파트경로당전라북도 전주시 완산구 태평3길70(태평동)아파트민영562007
경로당현황(2019년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
66706669전라북도부안군대리경로당전라북도 부안군 위도면 대장길 5단독민영351990
66716670전라북도부안군벌금경로당전라북도 부안군 위도면 벌금안길 16단독민영201989
66726671전라북도부안군벌금여자경로당전라북도 부안군 위도면 벌금안길 16단독민영302002
66736672전라북도부안군식도경로당전라북도 부안군 위도면 식도1길 15-2단독민영501989
66746673전라북도부안군전막경로당전라북도 부안군 위도면 위도로 1059-4단독민영301999
66756674전라북도부안군진리남자경로당전라북도 부안군 위도면 진리길 4단독민영401989
66766675전라북도부안군진리여자경로당전라북도 부안군 위도면 진리안길 23단독민영551995
66776676전라북도부안군치도남자경로당전라북도 부안군 위도면 위도로 1473단독민영301989
66786677전라북도부안군치도여자경로당전라북도 부안군 위도면 진리잔등로 128단독민영401994
66796678전라북도부안군파장금경로당전라북도 부안군 위도면 파장금길 8단독민영451991

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 4Unnamed: 5Unnamed: 6# duplicates
15전라북도무주군무주읍 주계로 92-3단독민간3
0전라북도고창군고수면 부곡길 129단독민영2
1전라북도고창군고창읍 월곡1길 43단독민영2
2전라북도군산시군산시 임피면 중전길 6단독민영2
3전라북도군산시전라북도 군산시 대야면 우덕1길 9시립민영2
4전라북도군산시전라북도 군산시 서당길 11, 현대A아파트민영2
5전라북도김제시금산면 송율길 242단독민간2
6전라북도김제시만경 3길 14복지회관민간2
7전라북도김제시하동1길 79아파트민간2
8전라북도김제시황산면 진흥3길 16단독민간2