Overview

Dataset statistics

Number of variables7
Number of observations3465
Missing cells3478
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory199.8 KiB
Average record size in memory59.0 B

Variable types

Unsupported2
Numeric2
Text2
Categorical1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15052/S/1/datasetView.do

Alerts

비고 (휴지/휴지시작연도) is highly imbalanced (95.3%)Imbalance
Unnamed: 0 has 3465 (100.0%) missing valuesMissing
연번 has unique valuesUnique
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
경로당 개설일 is an unsupported type, check if it needs cleaning or further analysisUnsupported
회원수 has 54 (1.6%) zerosZeros

Reproduction

Analysis started2024-03-13 12:56:47.269467
Analysis finished2024-03-13 12:56:49.056721
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3465
Missing (%)100.0%
Memory size30.6 KiB

연번
Real number (ℝ)

UNIQUE 

Distinct3465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1733
Minimum1
Maximum3465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.6 KiB
2024-03-13T21:56:49.142236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile174.2
Q1867
median1733
Q32599
95-th percentile3291.8
Maximum3465
Range3464
Interquartile range (IQR)1732

Descriptive statistics

Standard deviation1000.4037
Coefficient of variation (CV)0.57726698
Kurtosis-1.2
Mean1733
Median Absolute Deviation (MAD)866
Skewness0
Sum6004845
Variance1000807.5
MonotonicityStrictly increasing
2024-03-13T21:56:49.323551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2315 1
 
< 0.1%
2304 1
 
< 0.1%
2305 1
 
< 0.1%
2306 1
 
< 0.1%
2307 1
 
< 0.1%
2308 1
 
< 0.1%
2309 1
 
< 0.1%
2310 1
 
< 0.1%
2311 1
 
< 0.1%
Other values (3455) 3455
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3465 1
< 0.1%
3464 1
< 0.1%
3463 1
< 0.1%
3462 1
< 0.1%
3461 1
< 0.1%
3460 1
< 0.1%
3459 1
< 0.1%
3458 1
< 0.1%
3457 1
< 0.1%
3456 1
< 0.1%

경로당 명
Text

Distinct3295
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
2024-03-13T21:56:49.610533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length7.8253968
Min length2

Characters and Unicode

Total characters27115
Distinct characters500
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3178 ?
Unique (%)91.7%

Sample

1st row청 운
2nd row세종마을
3rd row사 직
4th row복 정
5th row삼 청
ValueCountFrequency (%)
경로당 140
 
3.6%
서초구립 32
 
0.8%
은평뉴타운상림마을 14
 
0.4%
은평뉴타운 11
 
0.3%
아 10
 
0.3%
제1 8
 
0.2%
중앙 7
 
0.2%
제2 7
 
0.2%
장수 7
 
0.2%
1단지 6
 
0.2%
Other values (3331) 3631
93.8%
2024-03-13T21:56:50.108756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 1793
 
6.6%
로 1783
 
6.6%
당 1782
 
6.6%
아 1526
 
5.6%
파 782
 
2.9%
( 775
 
2.9%
) 774
 
2.9%
트 725
 
2.7%
동 576
 
2.1%
499
 
1.8%
Other values (490) 16100
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22943
84.6%
Decimal Number 1245
 
4.6%
Open Punctuation 776
 
2.9%
Close Punctuation 775
 
2.9%
Uppercase Letter 665
 
2.5%
Space Separator 499
 
1.8%
Other Symbol 109
 
0.4%
Lowercase Letter 53
 
0.2%
Dash Punctuation 24
 
0.1%
Other Punctuation 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1793
 
7.8%
로 1783
 
7.8%
당 1782
 
7.8%
아 1526
 
6.7%
파 782
 
3.4%
트 725
 
3.2%
동 576
 
2.5%
지 475
 
2.1%
대 392
 
1.7%
단 361
 
1.6%
Other values (436) 12748
55.6%
Uppercase Letter
ValueCountFrequency (%)
A 370
55.6%
P 80
 
12.0%
T 76
 
11.4%
S 26
 
3.9%
H 19
 
2.9%
K 18
 
2.7%
C 17
 
2.6%
L 15
 
2.3%
D 8
 
1.2%
I 8
 
1.2%
Other values (8) 28
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 31
58.5%
l 6
 
11.3%
k 3
 
5.7%
c 3
 
5.7%
i 3
 
5.7%
s 2
 
3.8%
v 1
 
1.9%
h 1
 
1.9%
r 1
 
1.9%
a 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
2 388
31.2%
1 385
30.9%
3 153
 
12.3%
4 86
 
6.9%
5 63
 
5.1%
6 47
 
3.8%
0 40
 
3.2%
7 36
 
2.9%
9 26
 
2.1%
8 21
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 10
41.7%
, 5
20.8%
· 3
 
12.5%
․ 3
 
12.5%
' 1
 
4.2%
@ 1
 
4.2%
: 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 775
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 774
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
499
100.0%
Other Symbol
ValueCountFrequency (%)
㉵ 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23052
85.0%
Common 3345
 
12.3%
Latin 718
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1793
 
7.8%
로 1783
 
7.7%
당 1782
 
7.7%
아 1526
 
6.6%
파 782
 
3.4%
트 725
 
3.1%
동 576
 
2.5%
지 475
 
2.1%
대 392
 
1.7%
단 361
 
1.6%
Other values (437) 12857
55.8%
Latin
ValueCountFrequency (%)
A 370
51.5%
P 80
 
11.1%
T 76
 
10.6%
e 31
 
4.3%
S 26
 
3.6%
H 19
 
2.6%
K 18
 
2.5%
C 17
 
2.4%
L 15
 
2.1%
D 8
 
1.1%
Other values (19) 58
 
8.1%
Common
ValueCountFrequency (%)
( 775
23.2%
) 774
23.1%
499
14.9%
2 388
11.6%
1 385
11.5%
3 153
 
4.6%
4 86
 
2.6%
5 63
 
1.9%
6 47
 
1.4%
0 40
 
1.2%
Other values (14) 135
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22943
84.6%
ASCII 4057
 
15.0%
None 112
 
0.4%
Punctuation 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 1793
 
7.8%
로 1783
 
7.8%
당 1782
 
7.8%
아 1526
 
6.7%
파 782
 
3.4%
트 725
 
3.2%
동 576
 
2.5%
지 475
 
2.1%
대 392
 
1.7%
단 361
 
1.6%
Other values (436) 12748
55.6%
ASCII
ValueCountFrequency (%)
( 775
19.1%
) 774
19.1%
499
12.3%
2 388
9.6%
1 385
9.5%
A 370
9.1%
3 153
 
3.8%
4 86
 
2.1%
P 80
 
2.0%
T 76
 
1.9%
Other values (41) 471
11.6%
None
ValueCountFrequency (%)
㉵ 109
97.3%
· 3
 
2.7%
Punctuation
ValueCountFrequency (%)
․ 3
100.0%

주 소
Text

Distinct3392
Distinct (%)97.9%
Missing2
Missing (%)0.1%
Memory size27.2 KiB
2024-03-13T21:56:50.499594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length18.354606
Min length5

Characters and Unicode

Total characters63562
Distinct characters421
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3331 ?
Unique (%)96.2%

Sample

1st row종로구 필운대로 86 1층(신교동)
2nd row종로구 자하문로11길33(통인동)
3rd row종로구사직로9길 15-25(사직동)
4th row종로구 삼청로4길 22(삼청동)
5th row종로구 삼청로5길 30(팔판동)
ValueCountFrequency (%)
서울특별시 700
 
6.2%
구로구 197
 
1.8%
강남구 166
 
1.5%
서울시 161
 
1.4%
성동구 160
 
1.4%
동대문구 134
 
1.2%
중랑구 127
 
1.1%
강동구 120
 
1.1%
관악구 114
 
1.0%
서대문구 110
 
1.0%
Other values (5059) 9258
82.3%
2024-03-13T21:56:51.078126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8007
 
12.6%
로 3737
 
5.9%
1 3245
 
5.1%
동 2819
 
4.4%
길 2324
 
3.7%
2 2276
 
3.6%
) 1886
 
3.0%
( 1886
 
3.0%
구 1853
 
2.9%
3 1712
 
2.7%
Other values (411) 33817
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34714
54.6%
Decimal Number 15021
23.6%
Space Separator 8145
 
12.8%
Close Punctuation 1886
 
3.0%
Open Punctuation 1886
 
3.0%
Other Punctuation 965
 
1.5%
Dash Punctuation 770
 
1.2%
Control 136
 
0.2%
Uppercase Letter 29
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3737
 
10.8%
동 2819
 
8.1%
길 2324
 
6.7%
구 1853
 
5.3%
서 1235
 
3.6%
울 972
 
2.8%
시 922
 
2.7%
아 709
 
2.0%
별 702
 
2.0%
특 701
 
2.0%
Other values (377) 18740
54.0%
Decimal Number
ValueCountFrequency (%)
1 3245
21.6%
2 2276
15.2%
3 1712
11.4%
4 1366
9.1%
5 1329
8.8%
7 1127
 
7.5%
0 1127
 
7.5%
6 1125
 
7.5%
8 870
 
5.8%
9 844
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 6
20.7%
A 5
17.2%
B 4
13.8%
F 3
10.3%
K 3
10.3%
P 2
 
6.9%
T 2
 
6.9%
G 2
 
6.9%
H 1
 
3.4%
C 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 958
99.3%
. 5
 
0.5%
/ 1
 
0.1%
@ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
66.7%
k 1
 
16.7%
s 1
 
16.7%
Space Separator
ValueCountFrequency (%)
8007
98.3%
  138
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 1886
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1886
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 770
100.0%
Control
ValueCountFrequency (%)
136
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34714
54.6%
Common 28813
45.3%
Latin 35
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3737
 
10.8%
동 2819
 
8.1%
길 2324
 
6.7%
구 1853
 
5.3%
서 1235
 
3.6%
울 972
 
2.8%
시 922
 
2.7%
아 709
 
2.0%
별 702
 
2.0%
특 701
 
2.0%
Other values (377) 18740
54.0%
Common
ValueCountFrequency (%)
8007
27.8%
1 3245
11.3%
2 2276
 
7.9%
) 1886
 
6.5%
( 1886
 
6.5%
3 1712
 
5.9%
4 1366
 
4.7%
5 1329
 
4.6%
7 1127
 
3.9%
0 1127
 
3.9%
Other values (11) 4852
16.8%
Latin
ValueCountFrequency (%)
S 6
17.1%
A 5
14.3%
e 4
11.4%
B 4
11.4%
F 3
8.6%
K 3
8.6%
P 2
 
5.7%
T 2
 
5.7%
G 2
 
5.7%
H 1
 
2.9%
Other values (3) 3
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34714
54.6%
ASCII 28710
45.2%
None 138
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8007
27.9%
1 3245
11.3%
2 2276
 
7.9%
) 1886
 
6.6%
( 1886
 
6.6%
3 1712
 
6.0%
4 1366
 
4.8%
5 1329
 
4.6%
7 1127
 
3.9%
0 1127
 
3.9%
Other values (23) 4749
16.5%
Hangul
ValueCountFrequency (%)
로 3737
 
10.8%
동 2819
 
8.1%
길 2324
 
6.7%
구 1853
 
5.3%
서 1235
 
3.6%
울 972
 
2.8%
시 922
 
2.7%
아 709
 
2.0%
별 702
 
2.0%
특 701
 
2.0%
Other values (377) 18740
54.0%
None
ValueCountFrequency (%)
  138
100.0%

회원수
Real number (ℝ)

ZEROS 

Distinct142
Distinct (%)4.1%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean38.319931
Minimum0
Maximum400
Zeros54
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size30.6 KiB
2024-03-13T21:56:51.260987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q124
median33
Q346
95-th percentile78.2
Maximum400
Range400
Interquartile range (IQR)22

Descriptive statistics

Standard deviation24.162908
Coefficient of variation (CV)0.63055719
Kurtosis42.258593
Mean38.319931
Median Absolute Deviation (MAD)10
Skewness4.3016471
Sum132472
Variance583.84611
MonotonicityNot monotonic
2024-03-13T21:56:51.948247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 171
 
4.9%
25 134
 
3.9%
30 124
 
3.6%
21 124
 
3.6%
23 115
 
3.3%
22 115
 
3.3%
24 112
 
3.2%
28 103
 
3.0%
26 102
 
2.9%
32 99
 
2.9%
Other values (132) 2258
65.2%
ValueCountFrequency (%)
0 54
1.6%
2 1
 
< 0.1%
4 2
 
0.1%
7 1
 
< 0.1%
8 3
 
0.1%
9 1
 
< 0.1%
10 8
 
0.2%
11 10
 
0.3%
12 12
 
0.3%
13 9
 
0.3%
ValueCountFrequency (%)
400 1
< 0.1%
396 1
< 0.1%
320 1
< 0.1%
290 1
< 0.1%
254 1
< 0.1%
189 1
< 0.1%
186 1
< 0.1%
181 1
< 0.1%
176 1
< 0.1%
171 1
< 0.1%

경로당 개설일
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)0.1%
Memory size27.2 KiB

비고 (휴지/휴지시작연도)
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
<NA>
3396 
휴지/2018
 
15
휴지/2017
 
10
휴지
 
8
휴지/2014
 
5
Other values (20)
 
31

Length

Max length16
Median length4
Mean length4.0614719
Min length1

Unique

Unique14 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3396
98.0%
휴지/2018 15
 
0.4%
휴지/2017 10
 
0.3%
휴지 8
 
0.2%
휴지/2014 5
 
0.1%
휴지/2020 4
 
0.1%
휴지/2019 3
 
0.1%
휴지/2015 3
 
0.1%
휴지/2016 3
 
0.1%
휴지/2013 2
 
0.1%
Other values (15) 16
 
0.5%

Length

2024-03-13T21:56:52.204389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3396
97.9%
휴지/2018 15
 
0.4%
휴지/2017 10
 
0.3%
휴지 9
 
0.3%
휴지/2014 5
 
0.1%
휴지/2020 5
 
0.1%
휴지/2019 3
 
0.1%
휴지/2015 3
 
0.1%
휴지/2016 3
 
0.1%
중/2020 2
 
0.1%
Other values (17) 19
 
0.5%

Interactions

2024-03-13T21:56:48.347572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:56:48.075598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:56:48.482148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:56:48.200901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:56:52.343930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번회원수비고 (휴지/휴지시작연도)
연번1.0000.1600.716
회원수0.1601.0000.153
비고\n(휴지/휴지시작연도)0.7160.1531.000
2024-03-13T21:56:52.481767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번회원수비고 (휴지/휴지시작연도)
연번1.000-0.1200.310
회원수-0.1201.0000.380
비고\n(휴지/휴지시작연도)0.3100.3801.000

Missing values

2024-03-13T21:56:48.688401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:56:48.840842image/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.
2024-03-13T21:56:48.971809image/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

Unnamed: 0연번경로당 명주 소회원수경로당 개설일비고 (휴지/휴지시작연도)
0<NA>1청 운종로구 필운대로 86 1층(신교동)221997<NA>
1<NA>2세종마을종로구 자하문로11길33(통인동)492019<NA>
2<NA>3사 직종로구사직로9길 15-25(사직동)701993<NA>
3<NA>4복 정종로구 삼청로4길 22(삼청동)421974<NA>
4<NA>5삼 청종로구 삼청로5길 30(팔판동)291983<NA>
5<NA>6부 암종로구 자하문로 260(부암동)441968<NA>
6<NA>7신 영 (임차)종로구 세검정로6길 76-19(신영동)442018<NA>
7<NA>8구기할아버지종로구 진흥로 438-6(구기동)481978<NA>
8<NA>9구기할머니종로구 진흥로 438-8(구기동)502000<NA>
9<NA>10평 창종로구 평창문화로 48(평창동)471990<NA>
Unnamed: 0연번경로당 명주 소회원수경로당 개설일비고 (휴지/휴지시작연도)
3455<NA>3456둔촌현대1차A경로당서울특별시 강동구 동남로49길 57 (둔촌동, 현대1차아파트)221989-07-01 00:00:00<NA>
3456<NA>3457둔촌현대 3차A경로당서울특별시 강동구 진황도로 211(둔촌동, 현대3차아파트)211989-07-01 00:00:00<NA>
3457<NA>3458둔촌현대 4차 A경로당서울특별시 강동구 진황도로61길 7(둔촌동, 현대4차아파트)221996-12-21 00:00:00<NA>
3458<NA>3459신성둔촌미소지움1차A경로당서울특별시 강동구 명일로 102(둔촌동, 신성둔촌미소지움)191998-08-06 00:00:00<NA>
3459<NA>3460신성둔촌미소지움2차A경로당서울특별시 강동구 진황도로 212(둔촌동, 신성둔촌미소지움2차)202001-03-06 00:00:00<NA>
3460<NA>3461둔촌하이츠A경로당서울특별시 강동구 명일로 113(둔촌동, 둔촌하이츠아파트)321998-10-13 00:00:00<NA>
3461<NA>3462둔촌동아A경로당서울특별시 강동구 동남로49길 60-5(둔촌동, 동아아파트)241999-07-23 00:00:00<NA>
3462<NA>3463둔촌신동아A경로당서울특별시 강동구 양재대로96길 79(둔촌동, 둔촌신동아아파트)502003-04-15 00:00:00<NA>
3463<NA>3464한솔솔파크경로당서울특별시 강동구 천호대로198길 36(둔촌동, 둔촌한솔솔파크)332003-12-01 00:00:00<NA>
3464<NA>3465둔촌푸르지오A경로당서울특별시 강동구 명일로 172(둔촌동, 둔촌푸르지오아파트)272010-12-08 00:00:00<NA>