Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows14
Duplicate rows (%)0.1%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Numeric3
DateTime1
Text1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22189/F/1/datasetView.do

Alerts

Dataset has 14 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-23 01:33:56.984352
Analysis finished2024-03-23 01:34:02.330490
Duration5.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

민원접수일
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20231103
Minimum20231101
Maximum20231106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T10:34:02.425713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20231101
5-th percentile20231101
Q120231102
median20231103
Q320231104
95-th percentile20231105
Maximum20231106
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.476427
Coefficient of variation (CV)7.2978077 × 10-8
Kurtosis-1.1344839
Mean20231103
Median Absolute Deviation (MAD)1
Skewness-0.0050346427
Sum2.0231103 × 1011
Variance2.1798367
MonotonicityNot monotonic
2024-03-23T10:34:02.615833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20231104 2161
21.6%
20231105 1968
19.7%
20231103 1902
19.0%
20231102 1869
18.7%
20231101 1731
17.3%
20231106 369
 
3.7%
ValueCountFrequency (%)
20231101 1731
17.3%
20231102 1869
18.7%
20231103 1902
19.0%
20231104 2161
21.6%
20231105 1968
19.7%
20231106 369
 
3.7%
ValueCountFrequency (%)
20231106 369
 
3.7%
20231105 1968
19.7%
20231104 2161
21.6%
20231103 1902
19.0%
20231102 1869
18.7%
20231101 1731
17.3%

민원접수시간
Date

Distinct1339
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-23 00:00:00
Maximum2024-03-23 23:59:00
2024-03-23T10:34:02.857056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:03.179938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주소
Text

Distinct8458
Distinct (%)84.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T10:34:03.770772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length114
Median length88
Mean length20.713071
Min length4

Characters and Unicode

Total characters207110
Distinct characters751
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7563 ?
Unique (%)75.6%

Sample

1st row 신월동 509-8 골목 황금수산 앞
2nd row역삼동 777-32 / 논현로68길 23
3rd row서울특별시 성동구 고산자로 177
4th row서울특별시 마포구 도화2길 8
5th row곰달래로7길8-1 앞
ValueCountFrequency (%)
서울특별시 3641
 
8.4%
앞 1254
 
2.9%
서울 1041
 
2.4%
마포구 621
 
1.4%
용산구 614
 
1.4%
596
 
1.4%
서초구 491
 
1.1%
송파구 487
 
1.1%
중구 402
 
0.9%
양천구 395
 
0.9%
Other values (10595) 34018
78.1%
2024-03-23T10:34:04.767452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35533
 
17.2%
로 9431
 
4.6%
1 8835
 
4.3%
구 7244
 
3.5%
서 6455
 
3.1%
2 6221
 
3.0%
길 6108
 
2.9%
3 5357
 
2.6%
동 5292
 
2.6%
울 4858
 
2.3%
Other values (741) 111776
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118291
57.1%
Decimal Number 43634
 
21.1%
Space Separator 35533
 
17.2%
Dash Punctuation 3831
 
1.8%
Other Punctuation 2154
 
1.0%
Close Punctuation 1442
 
0.7%
Open Punctuation 1413
 
0.7%
Uppercase Letter 350
 
0.2%
Lowercase Letter 309
 
0.1%
Math Symbol 120
 
0.1%
Other values (2) 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9431
 
8.0%
구 7244
 
6.1%
서 6455
 
5.5%
길 6108
 
5.2%
동 5292
 
4.5%
울 4858
 
4.1%
시 3839
 
3.2%
특 3647
 
3.1%
별 3642
 
3.1%
대 2089
 
1.8%
Other values (657) 65686
55.5%
Uppercase Letter
ValueCountFrequency (%)
C 60
17.1%
S 40
11.4%
U 36
10.3%
G 27
 
7.7%
L 20
 
5.7%
B 20
 
5.7%
K 18
 
5.1%
I 16
 
4.6%
M 15
 
4.3%
A 15
 
4.3%
Other values (16) 83
23.7%
Lowercase Letter
ValueCountFrequency (%)
t 43
13.9%
k 37
12.0%
s 33
10.7%
o 31
10.0%
g 24
 
7.8%
p 21
 
6.8%
h 19
 
6.1%
m 13
 
4.2%
c 11
 
3.6%
l 9
 
2.9%
Other values (16) 68
22.0%
Decimal Number
ValueCountFrequency (%)
1 8835
20.2%
2 6221
14.3%
3 5357
12.3%
4 4146
9.5%
5 3826
8.8%
6 3717
8.5%
7 3227
 
7.4%
8 2878
 
6.6%
0 2828
 
6.5%
9 2599
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/ 1326
61.6%
* 326
 
15.1%
, 251
 
11.7%
. 184
 
8.5%
: 32
 
1.5%
? 20
 
0.9%
! 5
 
0.2%
& 5
 
0.2%
@ 4
 
0.2%
※ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 109
90.8%
> 8
 
6.7%
+ 2
 
1.7%
→ 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 1369
94.9%
] 73
 
5.1%
Open Punctuation
ValueCountFrequency (%)
( 1346
95.3%
[ 67
 
4.7%
Space Separator
ValueCountFrequency (%)
35533
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3831
100.0%
Control
ValueCountFrequency (%)
31
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118281
57.1%
Common 88160
42.6%
Latin 659
 
0.3%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9431
 
8.0%
구 7244
 
6.1%
서 6455
 
5.5%
길 6108
 
5.2%
동 5292
 
4.5%
울 4858
 
4.1%
시 3839
 
3.2%
특 3647
 
3.1%
별 3642
 
3.1%
대 2089
 
1.8%
Other values (656) 65676
55.5%
Latin
ValueCountFrequency (%)
C 60
 
9.1%
t 43
 
6.5%
S 40
 
6.1%
k 37
 
5.6%
U 36
 
5.5%
s 33
 
5.0%
o 31
 
4.7%
G 27
 
4.1%
g 24
 
3.6%
p 21
 
3.2%
Other values (42) 307
46.6%
Common
ValueCountFrequency (%)
35533
40.3%
1 8835
 
10.0%
2 6221
 
7.1%
3 5357
 
6.1%
4 4146
 
4.7%
- 3831
 
4.3%
5 3826
 
4.3%
6 3717
 
4.2%
7 3227
 
3.7%
8 2878
 
3.3%
Other values (22) 10589
 
12.0%
Han
ValueCountFrequency (%)
上 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118271
57.1%
ASCII 88817
42.9%
CJK 10
 
< 0.1%
Compat Jamo 10
 
< 0.1%
Punctuation 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35533
40.0%
1 8835
 
9.9%
2 6221
 
7.0%
3 5357
 
6.0%
4 4146
 
4.7%
- 3831
 
4.3%
5 3826
 
4.3%
6 3717
 
4.2%
7 3227
 
3.6%
8 2878
 
3.2%
Other values (72) 11246
 
12.7%
Hangul
ValueCountFrequency (%)
로 9431
 
8.0%
구 7244
 
6.1%
서 6455
 
5.5%
길 6108
 
5.2%
동 5292
 
4.5%
울 4858
 
4.1%
시 3839
 
3.2%
특 3647
 
3.1%
별 3642
 
3.1%
대 2089
 
1.8%
Other values (651) 65666
55.5%
CJK
ValueCountFrequency (%)
上 10
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 6
60.0%
ㄴ 1
 
10.0%
ㄷ 1
 
10.0%
ㅇ 1
 
10.0%
ㆍ 1
 
10.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

경도
Real number (ℝ)

Distinct9011
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98542
Minimum126.58185
Maximum127.72884
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T10:34:05.040074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58185
5-th percentile126.83864
Q1126.915
median126.99311
Q3127.04592
95-th percentile127.12898
Maximum127.72884
Range1.1469812
Interquartile range (IQR)0.13092347

Descriptive statistics

Standard deviation0.091131164
Coefficient of variation (CV)0.00071765064
Kurtosis2.8440016
Mean126.98542
Median Absolute Deviation (MAD)0.06740158
Skewness0.54441909
Sum1269854.2
Variance0.0083048891
MonotonicityNot monotonic
2024-03-23T10:34:05.293789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8515599 33
 
0.3%
127.566288213262 22
 
0.2%
126.947875788771 17
 
0.2%
126.896309478813 13
 
0.1%
126.948033283951 13
 
0.1%
126.89658614748 13
 
0.1%
126.89574742811 13
 
0.1%
126.921531136001 11
 
0.1%
126.986980299262 11
 
0.1%
126.91255092951 11
 
0.1%
Other values (9001) 9843
98.4%
ValueCountFrequency (%)
126.58185417555116 1
< 0.1%
126.783440969832 1
< 0.1%
126.8028883451633 1
< 0.1%
126.80300240997236 1
< 0.1%
126.80304254177383 1
< 0.1%
126.80327847721 1
< 0.1%
126.80331672182828 1
< 0.1%
126.80339450840488 1
< 0.1%
126.80632863789644 1
< 0.1%
126.8065014666428 1
< 0.1%
ValueCountFrequency (%)
127.728835362383 1
 
< 0.1%
127.566288213262 22
0.2%
127.18097661551298 1
 
< 0.1%
127.180837138837 2
 
< 0.1%
127.180835897276 1
 
< 0.1%
127.17938252474164 1
 
< 0.1%
127.17935980055738 1
 
< 0.1%
127.17928076272496 1
 
< 0.1%
127.176654612273 1
 
< 0.1%
127.175865600206 1
 
< 0.1%

위도
Real number (ℝ)

Distinct9012
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.538655
Minimum35.194069
Maximum37.863463
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T10:34:05.790196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.194069
5-th percentile37.478612
Q137.508303
median37.539356
Q337.562382
95-th percentile37.617317
Maximum37.863463
Range2.6693946
Interquartile range (IQR)0.0540796

Descriptive statistics

Standard deviation0.049160656
Coefficient of variation (CV)0.0013096009
Kurtosis518.01489
Mean37.538655
Median Absolute Deviation (MAD)0.026755642
Skewness-10.688398
Sum375386.55
Variance0.0024167701
MonotonicityNot monotonic
2024-03-23T10:34:06.028084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5042301 33
 
0.3%
37.2993621542091 22
 
0.2%
37.4862780245985 17
 
0.2%
37.4861289771301 13
 
0.1%
37.4661591268959 13
 
0.1%
37.4649476436525 13
 
0.1%
37.4658151649342 13
 
0.1%
37.5523693280482 11
 
0.1%
37.5577222466467 11
 
0.1%
37.5613659177411 11
 
0.1%
Other values (9002) 9843
98.4%
ValueCountFrequency (%)
35.1940689208393 1
 
< 0.1%
37.2993621542091 22
0.2%
37.3392735397088 1
 
< 0.1%
37.4393378019322 1
 
< 0.1%
37.4408873061763 1
 
< 0.1%
37.4419858283318 1
 
< 0.1%
37.4424735589159 2
 
< 0.1%
37.4424947533344 1
 
< 0.1%
37.4431934555646 1
 
< 0.1%
37.443974141741 2
 
< 0.1%
ValueCountFrequency (%)
37.8634634722747 1
< 0.1%
37.6917073351519 1
< 0.1%
37.6915496739459 1
< 0.1%
37.6875305 1
< 0.1%
37.6874771708146 1
< 0.1%
37.68733389972222 1
< 0.1%
37.6858749581621 1
< 0.1%
37.6845567 1
< 0.1%
37.6843274 1
< 0.1%
37.68395838888888 1
< 0.1%

Interactions

2024-03-23T10:34:01.352512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:00.040976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:00.723258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:01.512280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:00.221537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:00.985095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:01.681494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:00.464732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:01.178256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T10:34:06.177965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민원접수일경도위도
민원접수일1.0000.0510.014
경도0.0511.0000.891
위도0.0140.8911.000
2024-03-23T10:34:06.332565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민원접수일경도위도
민원접수일1.000-0.021-0.021
경도-0.0211.0000.025
위도-0.0210.0251.000

Missing values

2024-03-23T10:34:01.877210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T10:34:02.197569image/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

민원접수일민원접수시간주소경도위도
163562023110423:03:00신월동 509-8 골목 황금수산 앞126.84471437.522251
125332023110409:54:00역삼동 777-32 / 논현로68길 23127.04181637.495144
123362023110408:48:00서울특별시 성동구 고산자로 177127.0337437.55562
173552023110510:58:00서울특별시 마포구 도화2길 8126.9488837.540062
9572023110110:43:00곰달래로7길8-1 앞126.83536237.530629
19072023110115:27:00서울특별시 마포구 방울내로11길 198126.89620837.559005
7172023110109:39:00서울특별시 마포구 상암산로 34126.88876237.57622
127432023110410:37:00서울특별시 서초구 방배로 249126.98762437.495652
21712023110116:42:00(보라매동) 봉천로21길 42126.93435737.488849
123972023110409:11:00논현동 187-16 / 강남대로114길 41127.02740537.506629
민원접수일민원접수시간주소경도위도
162622023110422:27:00서울특별시 마포구 서강로3길 13126.93096937.549351
37492023110123:05:00서울특별시 서대문구 통일로 131126.96579737.566219
176022023110512:01:00화6/화곡로54길 48126.85118637.54974
86742023110310:40:00서울특별시 영등포구 도신로 116126.90503637.508067
68582023110219:36:00서울특별시 도봉구 도봉동 86-1127.0510137.681295
184562023110514:32:00회나무로 44길110126.993237.537539
93522023110313:37:00영등포구 경인로 882 (지번) 영등포동1가 113-1 후문 앞126.91071237.517521
165362023110500:30:00(성현동)은천로33길 36126.9531537.489157
91192023110312:29:00연희동 육정성과 이화원 앞쪽 보도126.92902137.566562
130992023110411:47:00뚝섬로 52가길 라인127.08092737.530974

Duplicate rows

Most frequently occurring

민원접수일민원접수시간주소경도위도# duplicates
02023110209:06:00서울특별시 구로구 고척로43길 15126.8515637.504232
12023110216:46:00서울특별시 구로구 고척로43길 15126.8515637.504232
22023110216:47:00서울특별시 구로구 고척로43길 15126.8515637.504232
32023110312:29:00서울특별시 구로구 고척로43길 15126.8515637.504232
42023110314:27:00서울특별시 구로구 고척로43길 15126.8515637.504232
52023110319:08:00서울특별시 송파구 마천로1길 14127.12342937.5110362
62023110408:29:00서울특별시 구로구 고척로43길 15126.8515637.504232
72023110410:10:00서초구 방배중앙로27길 36근처126.98370237.495312
82023110412:37:00신월동 513-6 카포스 옆 사이 골목126.84426337.5212822
92023110414:12:00서울특별시 구로구 고척로43길 15126.8515637.504232