Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows35
Duplicate rows (%)0.4%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

DateTime1
Text2
Categorical1
Numeric1

Dataset

Description경기도 포천시에서 웹팩스시스템에서 제공하는(일자별, 수신부서, 보낸번호, 수신번호, 수신된페이지수 등)데이터 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15091156/fileData.do

Alerts

상대방번호 has constant value ""Constant
Dataset has 35 (0.4%) duplicate rowsDuplicates
수신한페이지수 is highly skewed (γ1 = 23.18384449)Skewed

Reproduction

Analysis started2023-12-12 06:09:35.268131
Analysis finished2023-12-12 06:09:35.870765
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수신일자
Date

Distinct9354
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-01 00:59:00
Maximum2021-08-31 23:49:00
2023-12-12T15:09:35.963172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:09:36.151484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수신부서
Text

Distinct105
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:09:36.462461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length7.5849
Min length3

Characters and Unicode

Total characters75849
Distinct characters150
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row홍보전산과
2nd row영북면 총무팀
3rd row홍보전산과
4th row한탄강사업소
5th row식품안전과
ValueCountFrequency (%)
총무팀 1493
 
9.7%
민원팀 594
 
3.9%
환경지도과 593
 
3.9%
보건사업과 589
 
3.8%
소흘읍 517
 
3.4%
주민생활지원팀 507
 
3.3%
교통행정과 493
 
3.2%
홍보전산과 490
 
3.2%
축산과 386
 
2.5%
민원토지과과 378
 
2.5%
Other values (104) 9346
60.7%
2023-12-12T15:09:36.936679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7346
 
9.7%
6370
 
8.4%
팀 5008
 
6.6%
지 2891
 
3.8%
원 2628
 
3.5%
민 2564
 
3.4%
면 1807
 
2.4%
도 1757
 
2.3%
무 1662
 
2.2%
총 1645
 
2.2%
Other values (140) 42171
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68196
89.9%
Space Separator 6370
 
8.4%
Close Punctuation 502
 
0.7%
Open Punctuation 502
 
0.7%
Decimal Number 166
 
0.2%
Other Punctuation 113
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7346
 
10.8%
팀 5008
 
7.3%
지 2891
 
4.2%
원 2628
 
3.9%
민 2564
 
3.8%
면 1807
 
2.6%
도 1757
 
2.6%
무 1662
 
2.4%
총 1645
 
2.4%
정 1562
 
2.3%
Other values (134) 39326
57.7%
Decimal Number
ValueCountFrequency (%)
2 150
90.4%
4 16
 
9.6%
Space Separator
ValueCountFrequency (%)
6370
100.0%
Close Punctuation
ValueCountFrequency (%)
) 502
100.0%
Open Punctuation
ValueCountFrequency (%)
( 502
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68196
89.9%
Common 7653
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7346
 
10.8%
팀 5008
 
7.3%
지 2891
 
4.2%
원 2628
 
3.9%
민 2564
 
3.8%
면 1807
 
2.6%
도 1757
 
2.6%
무 1662
 
2.4%
총 1645
 
2.4%
정 1562
 
2.3%
Other values (134) 39326
57.7%
Common
ValueCountFrequency (%)
6370
83.2%
) 502
 
6.6%
( 502
 
6.6%
2 150
 
2.0%
/ 113
 
1.5%
4 16
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68196
89.9%
ASCII 7653
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7346
 
10.8%
팀 5008
 
7.3%
지 2891
 
4.2%
원 2628
 
3.9%
민 2564
 
3.8%
면 1807
 
2.6%
도 1757
 
2.6%
무 1662
 
2.4%
총 1645
 
2.4%
정 1562
 
2.3%
Other values (134) 39326
57.7%
ASCII
ValueCountFrequency (%)
6370
83.2%
) 502
 
6.6%
( 502
 
6.6%
2 150
 
2.0%
/ 113
 
1.5%
4 16
 
0.2%

상대방번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
031-***-****
10000 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-***-****
2nd row031-***-****
3rd row031-***-****
4th row031-***-****
5th row031-***-****

Common Values

ValueCountFrequency (%)
031-***-**** 10000
100.0%

Length

2023-12-12T15:09:37.069754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:37.169525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031 10000
100.0%

수신번호
Text

Distinct107
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:09:37.411822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row031-538-2742
2nd row031-538-4609
3rd row031-538-2742
4th row031-538-2995
5th row031-538-3685
ValueCountFrequency (%)
031-538-3247 593
 
5.9%
031-538-2742 473
 
4.7%
031-538-3865 386
 
3.9%
031-538-3085 363
 
3.6%
031-538-2299 339
 
3.4%
031-538-3266 338
 
3.4%
031-538-3635 336
 
3.4%
031-538-3466 308
 
3.1%
031-538-4139 301
 
3.0%
031-538-4829 290
 
2.9%
Other values (97) 6273
62.7%
2023-12-12T15:09:37.885473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 25576
21.3%
- 20000
16.7%
5 13907
11.6%
8 12562
10.5%
0 11806
9.8%
1 11103
9.3%
2 6197
 
5.2%
4 5893
 
4.9%
7 4787
 
4.0%
9 4202
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
83.3%
Dash Punctuation 20000
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 25576
25.6%
5 13907
13.9%
8 12562
12.6%
0 11806
11.8%
1 11103
11.1%
2 6197
 
6.2%
4 5893
 
5.9%
7 4787
 
4.8%
9 4202
 
4.2%
6 3967
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 25576
21.3%
- 20000
16.7%
5 13907
11.6%
8 12562
10.5%
0 11806
9.8%
1 11103
9.3%
2 6197
 
5.2%
4 5893
 
4.9%
7 4787
 
4.0%
9 4202
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 25576
21.3%
- 20000
16.7%
5 13907
11.6%
8 12562
10.5%
0 11806
9.8%
1 11103
9.3%
2 6197
 
5.2%
4 5893
 
4.9%
7 4787
 
4.0%
9 4202
 
3.5%

수신한페이지수
Real number (ℝ)

SKEWED 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.418
Minimum1
Maximum221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:09:38.052815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile7
Maximum221
Range220
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.7708219
Coefficient of variation (CV)1.5594797
Kurtosis1167.4866
Mean2.418
Median Absolute Deviation (MAD)0
Skewness23.183844
Sum24180
Variance14.219098
MonotonicityNot monotonic
2023-12-12T15:09:38.171790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 5529
55.3%
2 1852
 
18.5%
3 929
 
9.3%
4 508
 
5.1%
5 401
 
4.0%
6 223
 
2.2%
7 116
 
1.2%
8 79
 
0.8%
9 67
 
0.7%
10 55
 
0.5%
Other values (25) 241
 
2.4%
ValueCountFrequency (%)
1 5529
55.3%
2 1852
 
18.5%
3 929
 
9.3%
4 508
 
5.1%
5 401
 
4.0%
6 223
 
2.2%
7 116
 
1.2%
8 79
 
0.8%
9 67
 
0.7%
10 55
 
0.5%
ValueCountFrequency (%)
221 1
 
< 0.1%
67 1
 
< 0.1%
64 1
 
< 0.1%
59 2
 
< 0.1%
58 1
 
< 0.1%
49 1
 
< 0.1%
36 1
 
< 0.1%
33 1
 
< 0.1%
28 8
0.1%
26 4
< 0.1%

Interactions

2023-12-12T15:09:35.560222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T15:09:35.699679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:09:35.818877image/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

수신일자수신부서상대방번호수신번호수신한페이지수
351182021-07-12 16:55홍보전산과031-***-****031-538-27425
219222021-04-29 17:44영북면 총무팀031-***-****031-538-46093
346562021-07-09 17:07홍보전산과031-***-****031-538-27429
83062021-02-10 10:19한탄강사업소031-***-****031-538-29953
206742021-04-21 14:58식품안전과031-***-****031-538-36851
79262021-02-09 11:35기업지원과031-***-****031-538-27622
165672021-03-29 11:04친환경정책과031-***-****031-538-27532
89232021-02-15 14:16군내면 총무팀031-***-****031-538-42095
251202021-05-20 11:21소흘읍 민원팀031-***-****031-538-41391
143882021-03-15 19:37민원토지과과 지적팀031-***-****031-538-27512
수신일자수신부서상대방번호수신번호수신한페이지수
84032021-02-10 13:39여성가족과031-***-****031-538-32662
409222021-08-13 9:18상하수과 상수도팀031-***-****031-538-26001
98862021-02-18 14:04일동면 민원팀031-***-****031-538-45281
339012021-07-07 10:19홍보전산과031-***-****031-538-27425
413482021-08-17 17:26친환경정책과031-***-****031-538-27531
36712021-01-21 10:47교통행정과 교통지도팀031-***-****031-538-34661
50312021-01-28 10:17보건사업과 예방의약팀031-***-****031-538-36351
411582021-08-17 9:59환경지도과031-***-****031-538-32474
25062021-01-14 16:57친환경정책과031-***-****031-538-27531
77232021-02-08 15:46기업지원과031-***-****031-538-27623

Duplicate rows

Most frequently occurring

수신일자수신부서상대방번호수신번호수신한페이지수# duplicates
02021-01-07 15:36보건사업과 예방의약팀031-***-****031-538-363512
12021-01-14 15:54보건사업과 예방의약팀031-***-****031-538-363512
22021-01-19 10:28도서관정책과 일동도서관031-***-****031-538-393612
32021-02-01 10:42포천동 총무팀031-***-****031-538-477912
42021-02-01 16:16민원토지과과 지적팀031-***-****031-538-275112
52021-02-02 17:10교통행정과 차량등록팀031-***-****031-538-347812
62021-02-05 13:21환경지도과031-***-****031-538-324732
72021-02-08 12:50기업지원과031-***-****031-538-276222
82021-02-09 15:36선단동 총무팀031-***-****031-538-482912
92021-02-12 10:12자치행정과031-***-****031-538-274512