Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.6 KiB
Average record size in memory40.0 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15249/A/1/datasetView.do

Reproduction

Analysis started2024-05-18 01:16:37.855863
Analysis finished2024-05-18 01:17:37.921208
Duration1 minute and 0.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
송파구
769 
강서구
 
677
강남구
 
582
영등포구
 
545
서초구
 
534
Other values (23)
6893 

Length

Max length9
Median length3
Mean length3.0885
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row강서구
2nd row종로구
3rd row마포구
4th row관악구
5th row강동구

Common Values

ValueCountFrequency (%)
송파구 769
 
7.7%
강서구 677
 
6.8%
강남구 582
 
5.8%
영등포구 545
 
5.5%
서초구 534
 
5.3%
노원구 477
 
4.8%
마포구 447
 
4.5%
강동구 427
 
4.3%
종로구 421
 
4.2%
구로구 404
 
4.0%
Other values (18) 4717
47.2%

Length

2024-05-18T10:17:38.160170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 769
 
7.7%
강서구 677
 
6.8%
강남구 582
 
5.8%
영등포구 545
 
5.4%
서초구 534
 
5.3%
노원구 477
 
4.8%
마포구 447
 
4.5%
강동구 427
 
4.3%
종로구 421
 
4.2%
구로구 404
 
4.0%
Other values (21) 4722
47.2%

월
Text

Distinct2603
Distinct (%)26.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-18T10:17:38.788331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length29
Mean length15.448545
Min length3

Characters and Unicode

Total characters154470
Distinct characters597
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)1.0%

Sample

1st row1159. 서서울모터리움앞
2nd row461. 서울지방경찰청
3rd row425. DMC첨단산업센터
4th row2115. 관악농협농산물백화점
5th row1015. 샛마을 근린공원
ValueCountFrequency (%)
앞 2677
 
9.2%
출구 392
 
1.4%
옆 371
 
1.3%
입구 281
 
1.0%
1번출구 246
 
0.8%
교차로 233
 
0.8%
사거리 217
 
0.7%
2번출구 184
 
0.6%
뒤 170
 
0.6%
3번출구 158
 
0.5%
Other values (5175) 24028
83.0%
2024-05-18T10:17:39.975739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18958
 
12.3%
. 10020
 
6.5%
1 7636
 
4.9%
2 6150
 
4.0%
3 4995
 
3.2%
4 4647
 
3.0%
5 3623
 
2.3%
0 3538
 
2.3%
6 3471
 
2.2%
앞 3247
 
2.1%
Other values (587) 88185
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79500
51.5%
Decimal Number 42394
27.4%
Space Separator 18958
 
12.3%
Other Punctuation 10126
 
6.6%
Uppercase Letter 1471
 
1.0%
Open Punctuation 862
 
0.6%
Close Punctuation 862
 
0.6%
Lowercase Letter 199
 
0.1%
Dash Punctuation 66
 
< 0.1%
Math Symbol 15
 
< 0.1%
Other values (3) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 3247
 
4.1%
구 2974
 
3.7%
동 2237
 
2.8%
역 2198
 
2.8%
번 1876
 
2.4%
출 1847
 
2.3%
교 1602
 
2.0%
파 1476
 
1.9%
아 1392
 
1.8%
트 1360
 
1.7%
Other values (522) 59291
74.6%
Uppercase Letter
ValueCountFrequency (%)
K 194
13.2%
S 163
11.1%
T 131
 
8.9%
C 121
 
8.2%
A 102
 
6.9%
G 102
 
6.9%
L 89
 
6.1%
D 87
 
5.9%
M 76
 
5.2%
P 73
 
5.0%
Other values (14) 333
22.6%
Lowercase Letter
ValueCountFrequency (%)
e 62
31.2%
k 31
15.6%
s 26
13.1%
t 17
 
8.5%
n 12
 
6.0%
l 11
 
5.5%
a 6
 
3.0%
g 6
 
3.0%
y 6
 
3.0%
c 5
 
2.5%
Other values (6) 17
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 7636
18.0%
2 6150
14.5%
3 4995
11.8%
4 4647
11.0%
5 3623
8.5%
0 3538
8.3%
6 3471
8.2%
7 3104
7.3%
8 2782
 
6.6%
9 2448
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 10020
99.0%
, 59
 
0.6%
& 28
 
0.3%
? 12
 
0.1%
· 7
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 11
73.3%
+ 4
 
26.7%
Other Number
ValueCountFrequency (%)
② 2
66.7%
① 1
33.3%
Space Separator
ValueCountFrequency (%)
18958
100.0%
Open Punctuation
ValueCountFrequency (%)
( 862
100.0%
Close Punctuation
ValueCountFrequency (%)
) 862
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79504
51.5%
Common 73296
47.4%
Latin 1670
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 3247
 
4.1%
구 2974
 
3.7%
동 2237
 
2.8%
역 2198
 
2.8%
번 1876
 
2.4%
출 1847
 
2.3%
교 1602
 
2.0%
파 1476
 
1.9%
아 1392
 
1.8%
트 1360
 
1.7%
Other values (523) 59295
74.6%
Latin
ValueCountFrequency (%)
K 194
 
11.6%
S 163
 
9.8%
T 131
 
7.8%
C 121
 
7.2%
A 102
 
6.1%
G 102
 
6.1%
L 89
 
5.3%
D 87
 
5.2%
M 76
 
4.6%
P 73
 
4.4%
Other values (30) 532
31.9%
Common
ValueCountFrequency (%)
18958
25.9%
. 10020
13.7%
1 7636
10.4%
2 6150
 
8.4%
3 4995
 
6.8%
4 4647
 
6.3%
5 3623
 
4.9%
0 3538
 
4.8%
6 3471
 
4.7%
7 3104
 
4.2%
Other values (14) 7154
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79500
51.5%
ASCII 74956
48.5%
None 11
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18958
25.3%
. 10020
13.4%
1 7636
10.2%
2 6150
 
8.2%
3 4995
 
6.7%
4 4647
 
6.2%
5 3623
 
4.8%
0 3538
 
4.7%
6 3471
 
4.6%
7 3104
 
4.1%
Other values (51) 8814
11.8%
Hangul
ValueCountFrequency (%)
앞 3247
 
4.1%
구 2974
 
3.7%
동 2237
 
2.8%
역 2198
 
2.8%
번 1876
 
2.4%
출 1847
 
2.3%
교 1602
 
2.0%
파 1476
 
1.9%
아 1392
 
1.8%
트 1360
 
1.7%
Other values (522) 59291
74.6%
None
ValueCountFrequency (%)
· 7
63.6%
㈜ 4
36.4%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
66.7%
① 1
33.3%

일/월
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202112
1720 
202111
1680 
202110
1663 
202109
1656 
202108
1643 
Other values (2)
1638 

Length

Max length6
Median length6
Mean length5.9998
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row202109
2nd row202109
3rd row202112
4th row202109
5th row202111

Common Values

ValueCountFrequency (%)
202112 1720
17.2%
202111 1680
16.8%
202110 1663
16.6%
202109 1656
16.6%
202108 1643
16.4%
202107 1637
16.4%
<NA> 1
 
< 0.1%

Length

2024-05-18T10:17:40.603380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:17:41.162086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202112 1720
17.2%
202111 1680
16.8%
202110 1663
16.6%
202109 1656
16.6%
202108 1643
16.4%
202107 1637
16.4%
na 1
 
< 0.1%

202107 ~ 202112
Real number (ℝ)

Distinct3116
Distinct (%)31.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1223.1067
Minimum0
Maximum20191
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:17:41.574571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile157
Q1480
median919
Q31583
95-th percentile3274.3
Maximum20191
Range20191
Interquartile range (IQR)1103

Descriptive statistics

Standard deviation1148.497
Coefficient of variation (CV)0.93899987
Kurtosis21.66551
Mean1223.1067
Median Absolute Deviation (MAD)510
Skewness3.1869001
Sum12229844
Variance1319045.4
MonotonicityNot monotonic
2024-05-18T10:17:42.039992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
373 15
 
0.1%
765 14
 
0.1%
253 14
 
0.1%
365 13
 
0.1%
418 13
 
0.1%
429 13
 
0.1%
235 12
 
0.1%
665 12
 
0.1%
264 12
 
0.1%
945 12
 
0.1%
Other values (3106) 9869
98.7%
ValueCountFrequency (%)
0 8
0.1%
1 9
0.1%
2 6
0.1%
3 5
0.1%
4 4
< 0.1%
5 4
< 0.1%
6 2
 
< 0.1%
7 5
0.1%
8 2
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
20191 1
< 0.1%
14395 1
< 0.1%
13673 1
< 0.1%
13321 1
< 0.1%
11934 1
< 0.1%
11670 1
< 0.1%
11150 1
< 0.1%
10987 1
< 0.1%
10753 1
< 0.1%
10322 1
< 0.1%

Interactions

2024-05-18T10:16:40.959798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T10:17:42.344539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분일/월202107 ~ 202112
구분1.0000.0000.281
일/월0.0001.0000.165
202107 ~ 2021120.2810.1651.000
2024-05-18T10:17:42.579567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일/월구분
일/월1.0000.000
구분0.0001.000
2024-05-18T10:17:42.867579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
202107 ~ 202112구분일/월
202107 ~ 2021121.0000.1080.100
구분0.1081.0000.000
일/월0.1000.0001.000

Missing values

2024-05-18T10:17:37.086332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T10:17:37.461824image/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.
2024-05-18T10:17:37.766294image/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

구분월일/월202107 ~ 202112
5339강서구1159. 서서울모터리움앞202109974
7295종로구461. 서울지방경찰청2021091360
13840마포구425. DMC첨단산업센터202112587
5479관악구2115. 관악농협농산물백화점2021091617
10177강동구1015. 샛마을 근린공원202111653
11867양천구4523. 구립양천어르신요양센터20211194
7058용산구813. 삼각지역 3번출구2021091328
591광진구3586.군자역 비채온 오피스텔2021071884
14164성북구1306. 한성대입구역2번출구2021121085
5461강서구5055. 마곡역5번출구앞202109735
구분월일/월202107 ~ 202112
3965성동구4362. 행당중학교 후문202108885
13920서대문구3124.DMC센트럴아이파크아파트202112845
13095관악구2145. 은천초등학교 육교202112591
6374서초구2293. SPC 앞202109956
2649강동구1021. 강일동 리슈빌 빌딩앞2021081981
6708송파구2633.송파학사 옆2021091522
7936강서구3760. 발산역 8번 출구2021101688
412강서구2713.우장초등학교 앞2021071410
13584도봉구4074. 도봉구육아종합지원센터(창동)202112498
5690구로구2807.항동지구 1단지 105동 앞202109328