Overview

Dataset statistics

Number of variables8
Number of observations246
Missing cells8
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory67.5 B

Variable types

Numeric3
Categorical1
Text3
DateTime1

Dataset

Description노원구의 경로당에 대한 데이터로 행정동, 경로당명, 도로명주소, 전화번호, 면적, 회원수, 기준일자 등의 항목을 제공합니다.
Author서울특별시 노원구
URLhttps://www.data.go.kr/data/3072636/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
전화번호 has 8 (3.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:31:31.158465
Analysis finished2023-12-12 23:31:32.313016
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.5
Minimum1
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T08:31:32.381149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.25
Q162.25
median123.5
Q3184.75
95-th percentile233.75
Maximum246
Range245
Interquartile range (IQR)122.5

Descriptive statistics

Standard deviation71.158274
Coefficient of variation (CV)0.57618036
Kurtosis-1.2
Mean123.5
Median Absolute Deviation (MAD)61.5
Skewness0
Sum30381
Variance5063.5
MonotonicityStrictly increasing
2023-12-13T08:31:32.512356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
156 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
Other values (236) 236
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%

행정동
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
상계1동
26 
공릉2동
23 
공릉1동
18 
중계본동
17 
월계2동
16 
Other values (33)
146 

Length

Max length10
Median length4
Mean length4.597561
Min length4

Unique

Unique19 ?
Unique (%)7.7%

Sample

1st row월계1동(17)
2nd row월계1동
3rd row월계1동
4th row월계1동
5th row월계1동

Common Values

ValueCountFrequency (%)
상계1동 26
 
10.6%
공릉2동 23
 
9.3%
공릉1동 18
 
7.3%
중계본동 17
 
6.9%
월계2동 16
 
6.5%
월계1동 16
 
6.5%
상계3·4동 14
 
5.7%
중계4동 13
 
5.3%
상계2동 12
 
4.9%
월계3동 11
 
4.5%
Other values (28) 80
32.5%

Length

2023-12-13T08:31:32.676745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상계1동 26
 
10.6%
공릉2동 23
 
9.3%
공릉1동 18
 
7.3%
중계본동 17
 
6.9%
월계2동 16
 
6.5%
월계1동 16
 
6.5%
상계3·4동 14
 
5.7%
중계4동 13
 
5.3%
상계2동 12
 
4.9%
월계3동 11
 
4.5%
Other values (28) 80
32.5%

경로당명
Text

Distinct236
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T08:31:32.849941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length9.1747967
Min length5

Characters and Unicode

Total characters2257
Distinct characters199
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)92.3%

Sample

1st row월계1동경로당
2nd row월성경로당
3rd row벼루마을경로당
4th row광운경로당
5th row선곡경로당
ValueCountFrequency (%)
현대2차아파트경로당 3
 
1.2%
현대1차아파트경로당 2
 
0.8%
대동아파트경로당 2
 
0.8%
삼창아파트경로당 2
 
0.8%
주공6단지경로당 2
 
0.8%
중앙하이츠아파트경로당 2
 
0.8%
미성아파트경로당 2
 
0.8%
희망경로당 2
 
0.8%
상계대림아파트경로당 2
 
0.8%
동신아파트경로당 2
 
0.8%
Other values (228) 228
91.6%
2023-12-13T08:31:33.199462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 249
 
11.0%
로 248
 
11.0%
당 246
 
10.9%
아 149
 
6.6%
트 145
 
6.4%
파 141
 
6.2%
지 65
 
2.9%
단 52
 
2.3%
계 50
 
2.2%
공 42
 
1.9%
Other values (189) 870
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2133
94.5%
Decimal Number 114
 
5.1%
Other Punctuation 4
 
0.2%
Space Separator 3
 
0.1%
Lowercase Letter 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 249
 
11.7%
로 248
 
11.6%
당 246
 
11.5%
아 149
 
7.0%
트 145
 
6.8%
파 141
 
6.6%
지 65
 
3.0%
단 52
 
2.4%
계 50
 
2.3%
공 42
 
2.0%
Other values (173) 746
35.0%
Decimal Number
ValueCountFrequency (%)
1 37
32.5%
2 26
22.8%
3 12
 
10.5%
0 8
 
7.0%
4 8
 
7.0%
6 7
 
6.1%
7 6
 
5.3%
5 4
 
3.5%
9 4
 
3.5%
8 2
 
1.8%
Other Punctuation
ValueCountFrequency (%)
· 3
75.0%
, 1
 
25.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2133
94.5%
Common 121
 
5.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 249
 
11.7%
로 248
 
11.6%
당 246
 
11.5%
아 149
 
7.0%
트 145
 
6.8%
파 141
 
6.6%
지 65
 
3.0%
단 52
 
2.4%
계 50
 
2.3%
공 42
 
2.0%
Other values (173) 746
35.0%
Common
ValueCountFrequency (%)
1 37
30.6%
2 26
21.5%
3 12
 
9.9%
0 8
 
6.6%
4 8
 
6.6%
6 7
 
5.8%
7 6
 
5.0%
5 4
 
3.3%
9 4
 
3.3%
· 3
 
2.5%
Other values (3) 6
 
5.0%
Latin
ValueCountFrequency (%)
k 1
33.3%
B 1
33.3%
s 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2133
94.5%
ASCII 121
 
5.4%
None 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 249
 
11.7%
로 248
 
11.6%
당 246
 
11.5%
아 149
 
7.0%
트 145
 
6.8%
파 141
 
6.6%
지 65
 
3.0%
단 52
 
2.4%
계 50
 
2.3%
공 42
 
2.0%
Other values (173) 746
35.0%
ASCII
ValueCountFrequency (%)
1 37
30.6%
2 26
21.5%
3 12
 
9.9%
0 8
 
6.6%
4 8
 
6.6%
6 7
 
5.8%
7 6
 
5.0%
5 4
 
3.3%
9 4
 
3.3%
3
 
2.5%
Other values (5) 6
 
5.0%
None
ValueCountFrequency (%)
· 3
100.0%

도로명주소
Text

Distinct245
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T08:31:33.484837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length22.573171
Min length8

Characters and Unicode

Total characters5553
Distinct characters197
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

Unique244 ?
Unique (%)99.2%

Sample

1st row석계로8가길 2(월계동)
2nd row광운로13길 9 (월계동)
3rd row월계로44길 62(월계동)
4th row광운로19가길 53(월계동)
5th row광운로2길 15-6(월계동)
ValueCountFrequency (%)
섬밭로 12
 
1.7%
덕릉로 10
 
1.4%
한글비석로 10
 
1.4%
노원로 9
 
1.3%
공릉로 7
 
1.0%
중계로8길 6
 
0.8%
마들로 4
 
0.6%
중계로 4
 
0.6%
덕릉로60길 4
 
0.6%
수락산로 3
 
0.4%
Other values (553) 646
90.3%
2023-12-13T08:31:33.899233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
470
 
8.5%
동 321
 
5.8%
계 292
 
5.3%
로 247
 
4.4%
) 243
 
4.4%
( 243
 
4.4%
, 220
 
4.0%
1 217
 
3.9%
2 206
 
3.7%
아 206
 
3.7%
Other values (187) 2888
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3265
58.8%
Decimal Number 1082
 
19.5%
Space Separator 470
 
8.5%
Close Punctuation 243
 
4.4%
Open Punctuation 243
 
4.4%
Other Punctuation 220
 
4.0%
Dash Punctuation 27
 
0.5%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 321
 
9.8%
계 292
 
8.9%
로 247
 
7.6%
아 206
 
6.3%
트 200
 
6.1%
파 196
 
6.0%
길 175
 
5.4%
상 119
 
3.6%
릉 114
 
3.5%
공 104
 
3.2%
Other values (169) 1291
39.5%
Decimal Number
ValueCountFrequency (%)
1 217
20.1%
2 206
19.0%
3 117
10.8%
4 100
9.2%
5 94
8.7%
6 76
 
7.0%
8 75
 
6.9%
9 71
 
6.6%
7 69
 
6.4%
0 57
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
470
100.0%
Close Punctuation
ValueCountFrequency (%)
) 243
100.0%
Open Punctuation
ValueCountFrequency (%)
( 243
100.0%
Other Punctuation
ValueCountFrequency (%)
, 220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3265
58.8%
Common 2285
41.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 321
 
9.8%
계 292
 
8.9%
로 247
 
7.6%
아 206
 
6.3%
트 200
 
6.1%
파 196
 
6.0%
길 175
 
5.4%
상 119
 
3.6%
릉 114
 
3.5%
공 104
 
3.2%
Other values (169) 1291
39.5%
Common
ValueCountFrequency (%)
470
20.6%
) 243
10.6%
( 243
10.6%
, 220
9.6%
1 217
9.5%
2 206
9.0%
3 117
 
5.1%
4 100
 
4.4%
5 94
 
4.1%
6 76
 
3.3%
Other values (5) 299
13.1%
Latin
ValueCountFrequency (%)
k 1
33.3%
s 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3265
58.8%
ASCII 2288
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
470
20.5%
) 243
10.6%
( 243
10.6%
, 220
9.6%
1 217
9.5%
2 206
9.0%
3 117
 
5.1%
4 100
 
4.4%
5 94
 
4.1%
6 76
 
3.3%
Other values (8) 302
13.2%
Hangul
ValueCountFrequency (%)
동 321
 
9.8%
계 292
 
8.9%
로 247
 
7.6%
아 206
 
6.3%
트 200
 
6.1%
파 196
 
6.0%
길 175
 
5.4%
상 119
 
3.6%
릉 114
 
3.5%
공 104
 
3.2%
Other values (169) 1291
39.5%

전화번호
Text

MISSING 

Distinct238
Distinct (%)100.0%
Missing8
Missing (%)3.3%
Memory size2.1 KiB
2023-12-13T08:31:34.256811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.2310924
Min length8

Characters and Unicode

Total characters1959
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)100.0%

Sample

1st row917-2733
2nd row917-3776
3rd row943-8243
4th row942-7009
5th row912-8956
ValueCountFrequency (%)
911-0284 1
 
0.4%
952-6563 1
 
0.4%
952-8088 1
 
0.4%
952-4415 1
 
0.4%
932-9776 1
 
0.4%
935-6575 1
 
0.4%
939-2559 1
 
0.4%
938-7666 1
 
0.4%
930-3443(관리실 1
 
0.4%
952-0734 1
 
0.4%
Other values (228) 228
95.8%
2023-12-13T08:31:34.688765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 342
17.5%
- 240
12.3%
3 227
11.6%
7 187
9.5%
6 156
8.0%
2 138
7.0%
5 136
 
6.9%
0 132
 
6.7%
1 131
 
6.7%
8 128
 
6.5%
Other values (11) 142
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1698
86.7%
Dash Punctuation 240
 
12.3%
Other Letter 13
 
0.7%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 342
20.1%
3 227
13.4%
7 187
11.0%
6 156
9.2%
2 138
8.1%
5 136
 
8.0%
0 132
 
7.8%
1 131
 
7.7%
8 128
 
7.5%
4 121
 
7.1%
Other Letter
ValueCountFrequency (%)
관 3
23.1%
리 3
23.1%
실 2
15.4%
회 1
 
7.7%
장 1
 
7.7%
사 1
 
7.7%
무 1
 
7.7%
소 1
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1946
99.3%
Hangul 13
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
9 342
17.6%
- 240
12.3%
3 227
11.7%
7 187
9.6%
6 156
8.0%
2 138
7.1%
5 136
 
7.0%
0 132
 
6.8%
1 131
 
6.7%
8 128
 
6.6%
Other values (3) 129
 
6.6%
Hangul
ValueCountFrequency (%)
관 3
23.1%
리 3
23.1%
실 2
15.4%
회 1
 
7.7%
장 1
 
7.7%
사 1
 
7.7%
무 1
 
7.7%
소 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1946
99.3%
Hangul 13
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 342
17.6%
- 240
12.3%
3 227
11.7%
7 187
9.6%
6 156
8.0%
2 138
7.1%
5 136
 
7.0%
0 132
 
6.8%
1 131
 
6.7%
8 128
 
6.6%
Other values (3) 129
 
6.6%
Hangul
ValueCountFrequency (%)
관 3
23.1%
리 3
23.1%
실 2
15.4%
회 1
 
7.7%
장 1
 
7.7%
사 1
 
7.7%
무 1
 
7.7%
소 1
 
7.7%

면적(m2)
Real number (ℝ)

Distinct223
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.00541
Minimum21
Maximum496.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T08:31:35.066854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile37.635
Q168.1575
median100.61
Q3148.8
95-th percentile284.4825
Maximum496.97
Range475.97
Interquartile range (IQR)80.6425

Descriptive statistics

Standard deviation78.643477
Coefficient of variation (CV)0.6445901
Kurtosis2.5558273
Mean122.00541
Median Absolute Deviation (MAD)39
Skewness1.5067702
Sum30013.33
Variance6184.7964
MonotonicityNot monotonic
2023-12-13T08:31:35.206120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72.0 5
 
2.0%
128.0 4
 
1.6%
237.0 3
 
1.2%
81.0 3
 
1.2%
100.0 2
 
0.8%
105.0 2
 
0.8%
132.0 2
 
0.8%
133.0 2
 
0.8%
252.0 2
 
0.8%
165.0 2
 
0.8%
Other values (213) 219
89.0%
ValueCountFrequency (%)
21.0 1
0.4%
24.88 1
0.4%
30.24 1
0.4%
30.57 1
0.4%
30.6 1
0.4%
34.56 1
0.4%
35.28 1
0.4%
35.73 1
0.4%
36.0 2
0.8%
36.56 1
0.4%
ValueCountFrequency (%)
496.97 1
0.4%
393.37 1
0.4%
343.18 1
0.4%
338.0 1
0.4%
334.0 1
0.4%
331.0 1
0.4%
328.98 1
0.4%
323.4 1
0.4%
320.0 1
0.4%
316.0 1
0.4%

회원수
Real number (ℝ)

Distinct54
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.04065
Minimum17
Maximum192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T08:31:35.331475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile21
Q124
median29
Q336.75
95-th percentile59.75
Maximum192
Range175
Interquartile range (IQR)12.75

Descriptive statistics

Standard deviation18.54257
Coefficient of variation (CV)0.54471845
Kurtosis27.019491
Mean34.04065
Median Absolute Deviation (MAD)6
Skewness4.3306623
Sum8374
Variance343.82691
MonotonicityNot monotonic
2023-12-13T08:31:35.466788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 18
 
7.3%
25 17
 
6.9%
24 14
 
5.7%
22 13
 
5.3%
26 13
 
5.3%
30 13
 
5.3%
21 12
 
4.9%
31 12
 
4.9%
29 11
 
4.5%
27 11
 
4.5%
Other values (44) 112
45.5%
ValueCountFrequency (%)
17 2
 
0.8%
18 1
 
0.4%
19 2
 
0.8%
20 3
 
1.2%
21 12
4.9%
22 13
5.3%
23 18
7.3%
24 14
5.7%
25 17
6.9%
26 13
5.3%
ValueCountFrequency (%)
192 1
0.4%
137 1
0.4%
113 1
0.4%
105 1
0.4%
100 1
0.4%
95 1
0.4%
86 1
0.4%
71 1
0.4%
68 1
0.4%
67 1
0.4%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2022-08-16 00:00:00
Maximum2022-08-16 00:00:00
2023-12-13T08:31:35.595958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:35.720041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:31:31.920059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.528940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.724120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.988804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.592650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.788449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:32.060173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.655827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:31.853739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:31:35.807120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동면적(m2)회원수
연번1.0000.9790.3170.217
행정동0.9791.0000.8130.214
면적(m2)0.3170.8131.0000.289
회원수0.2170.2140.2891.000
2023-12-13T08:31:35.906904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(m2)회원수행정동
연번1.0000.1920.0020.797
면적(m2)0.1921.0000.3570.433
회원수0.0020.3571.0000.074
행정동0.7970.4330.0741.000

Missing values

2023-12-13T08:31:32.165268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:31:32.271504image/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

연번행정동경로당명도로명주소전화번호면적(m2)회원수기준일자
01월계1동(17)월계1동경로당석계로8가길 2(월계동)917-2733496.97422022-08-16
12월계1동월성경로당광운로13길 9 (월계동)917-3776128.0362022-08-16
23월계1동벼루마을경로당월계로44길 62(월계동)943-8243125.26492022-08-16
34월계1동광운경로당광운로19가길 53(월계동)942-700956.0332022-08-16
45월계1동선곡경로당광운로2길 15-6(월계동)912-895662.0372022-08-16
56월계1동동신아파트경로당광운로2나길 30(월계동, 동신아파트)918-2056119.0442022-08-16
67월계1동삼창아파트경로당광운로2나길 50(월계동, 삼창아파트)909-462380.0262022-08-16
78월계1동대동아파트경로당광운로 46(월계동, 대동아파트)913-607297.3302022-08-16
89월계1동월계한일1차아파트경로당석계로15길 25(월계동, 한일아파트)919-803563.0272022-08-16
910월계1동월계현대아파트경로당석계로 49(월계동, 현대아파트)942-2407233.34262022-08-16
연번행정동경로당명도로명주소전화번호면적(m2)회원수기준일자
236237상계8동주공16단지경로당동일로227길 86(상계동, 상계주공16단지아파트)939-4223334.0432022-08-16
237238상계9동(4)주공12단지경로당한글비석로 530(상계동, 상계주공12단지아파트)935-8129220.0232022-08-16
238239상계9동주공13단지경로당한글비석로54길 92(상계동, 상계주공13단지아파트)931-2968124.0252022-08-16
239240상계9동보람아파트경로당한글비석로 479(상계동, 보람아파트1단지)934-0991209.0682022-08-16
240241상계9동주공14단지경로당동일로228길 23(상계동, 상계주공14단지아파트)938-0888310.72572022-08-16
241242상계10동(5)주공7단지경로당동일로 1456(상계동, 상계주공7단지아파트)939-5221320.0432022-08-16
242243상계10동주공9단지경로당노원로 532(상계동, 상계주공9단지아파트)938-4179316.0402022-08-16
243244상계10동대림아파트경로당동일로221길 22(상계동, 대림아파트)938-831669.89252022-08-16
244245상계10동임광아파트경로당노원로 569(상계동, 임광아파트)939-759171.0242022-08-16
245246상계10동포레나노원아파트경로당노원로38길 76 시니어클럽하우스02-3392-4938393.37312022-08-16