Overview

Dataset statistics

Number of variables10
Number of observations1785
Missing cells3568
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory143.1 KiB
Average record size in memory82.1 B

Variable types

Numeric1
Categorical4
Text2
DateTime3

Dataset

Description인천광역시 문자발송시스템 발송 현황입니다.
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15083728/fileData.do

Alerts

발송건수 has constant value ""Constant
발송상태 has constant value ""Constant
발신부서 has constant value ""Constant
발신자 has constant value ""Constant
번호 is highly overall correlated with 메시지 종류High correlation
발신번호 is highly overall correlated with 메시지 종류High correlation
메시지 종류 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
발신번호 is highly imbalanced (58.9%)Imbalance
발신부서 has 1784 (99.9%) missing valuesMissing
발신자 has 1784 (99.9%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:29:50.644547
Analysis finished2023-12-12 07:29:51.485967
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1785
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean893
Minimum1
Maximum1785
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-12-12T16:29:51.568116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile90.2
Q1447
median893
Q31339
95-th percentile1695.8
Maximum1785
Range1784
Interquartile range (IQR)892

Descriptive statistics

Standard deviation515.42943
Coefficient of variation (CV)0.57718861
Kurtosis-1.2
Mean893
Median Absolute Deviation (MAD)446
Skewness0
Sum1594005
Variance265667.5
MonotonicityStrictly increasing
2023-12-12T16:29:51.719449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1187 1
 
0.1%
1198 1
 
0.1%
1197 1
 
0.1%
1196 1
 
0.1%
1195 1
 
0.1%
1194 1
 
0.1%
1193 1
 
0.1%
1192 1
 
0.1%
1191 1
 
0.1%
Other values (1775) 1775
99.4%
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 (%)
1785 1
0.1%
1784 1
0.1%
1783 1
0.1%
1782 1
0.1%
1781 1
0.1%
1780 1
0.1%
1779 1
0.1%
1778 1
0.1%
1777 1
0.1%
1776 1
0.1%

발신번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
032-509-8940
1279 
032-504-2114
429 
032-509-8410
 
68
032-509-6442
 
6
032-509-8350
 
2

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row032-509-8940
2nd row032-509-8940
3rd row032-509-8940
4th row032-509-8940
5th row032-509-8940

Common Values

ValueCountFrequency (%)
032-509-8940 1279
71.7%
032-504-2114 429
 
24.0%
032-509-8410 68
 
3.8%
032-509-6442 6
 
0.3%
032-509-8350 2
 
0.1%
032-509-6395 1
 
0.1%

Length

2023-12-12T16:29:51.919459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:29:52.072816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
032-509-8940 1279
71.7%
032-504-2114 429
 
24.0%
032-509-8410 68
 
3.8%
032-509-6442 6
 
0.3%
032-509-8350 2
 
0.1%
032-509-6395 1
 
0.1%

메시지 종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
lms
1065 
sms
720 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlms
2nd rowsms
3rd rowsms
4th rowlms
5th rowsms

Common Values

ValueCountFrequency (%)
lms 1065
59.7%
sms 720
40.3%

Length

2023-12-12T16:29:52.253297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:29:52.658690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
lms 1065
59.7%
sms 720
40.3%

발송건수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
1
1785 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1785
100.0%

Length

2023-12-12T16:29:52.774313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:29:52.894121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1785
100.0%

발송상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
발송완료
1785 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row발송완료
2nd row발송완료
3rd row발송완료
4th row발송완료
5th row발송완료

Common Values

ValueCountFrequency (%)
발송완료 1785
100.0%

Length

2023-12-12T16:29:53.018062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:29:53.122915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
발송완료 1785
100.0%

발신부서
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1784
Missing (%)99.9%
Memory size14.1 KiB
2023-12-12T16:29:53.229472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row홈페이지관리
ValueCountFrequency (%)
홈페이지관리 1
100.0%
2023-12-12T16:29:53.476135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
홈 1
16.7%
페 1
16.7%
이 1
16.7%
지 1
16.7%
관 1
16.7%
리 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홈 1
16.7%
페 1
16.7%
이 1
16.7%
지 1
16.7%
관 1
16.7%
리 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홈 1
16.7%
페 1
16.7%
이 1
16.7%
지 1
16.7%
관 1
16.7%
리 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
홈 1
16.7%
페 1
16.7%
이 1
16.7%
지 1
16.7%
관 1
16.7%
리 1
16.7%

발신자
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1784
Missing (%)99.9%
Memory size14.1 KiB
2023-12-12T16:29:53.609171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row통합홍보요청
ValueCountFrequency (%)
통합홍보요청 1
100.0%
2023-12-12T16:29:53.830346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
통 1
16.7%
합 1
16.7%
홍 1
16.7%
보 1
16.7%
요 1
16.7%
청 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 1
16.7%
합 1
16.7%
홍 1
16.7%
보 1
16.7%
요 1
16.7%
청 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 1
16.7%
합 1
16.7%
홍 1
16.7%
보 1
16.7%
요 1
16.7%
청 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
통 1
16.7%
합 1
16.7%
홍 1
16.7%
보 1
16.7%
요 1
16.7%
청 1
16.7%

등록일
Date

Distinct1780
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
Minimum2021-01-11 09:00:57
Maximum2021-05-24 18:01:30
2023-12-12T16:29:53.939348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:29:54.049188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발송예정일
Date

Distinct1780
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
Minimum2021-01-11 09:00:57
Maximum2021-05-24 18:01:30
2023-12-12T16:29:54.162397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:29:54.276989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발송완료일
Date

Distinct1780
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size14.1 KiB
Minimum2021-01-11 09:00:59
Maximum2021-05-24 18:01:30
2023-12-12T16:29:54.382592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:29:54.503722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T16:29:50.940083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:29:54.574682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발신번호메시지 종류
번호1.0000.6420.698
발신번호0.6421.0000.695
메시지 종류0.6980.6951.000
2023-12-12T16:29:54.642453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메시지 종류발신번호
메시지 종류1.0000.510
발신번호0.5101.000
2023-12-12T16:29:54.715552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발신번호메시지 종류
번호1.0000.4060.544
발신번호0.4061.0000.510
메시지 종류0.5440.5101.000

Missing values

2023-12-12T16:29:51.091143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:29:51.280908image/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.
2023-12-12T16:29:51.421452image/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

번호발신번호메시지 종류발송건수발송상태발신부서발신자등록일발송예정일발송완료일
01032-509-8940lms1발송완료<NA><NA>2021-05-24 18:01:302021-05-24 18:01:302021-05-24 18:01:30
12032-509-8940sms1발송완료<NA><NA>2021-05-24 17:07:332021-05-24 17:07:332021-05-24 17:07:34
23032-509-8940sms1발송완료<NA><NA>2021-05-24 16:44:262021-05-24 16:44:262021-05-24 16:44:26
34032-509-8940lms1발송완료<NA><NA>2021-05-24 16:02:162021-05-24 16:02:162021-05-24 16:02:16
45032-509-8940sms1발송완료<NA><NA>2021-05-24 15:10:302021-05-24 15:10:302021-05-24 15:10:31
56032-509-8940lms1발송완료<NA><NA>2021-05-24 14:55:142021-05-24 14:55:142021-05-24 14:55:14
67032-509-8940sms1발송완료<NA><NA>2021-05-24 14:54:562021-05-24 14:54:562021-05-24 14:54:56
78032-509-8940sms1발송완료<NA><NA>2021-05-24 14:54:242021-05-24 14:54:242021-05-24 14:54:24
89032-509-8940lms1발송완료<NA><NA>2021-05-24 14:14:512021-05-24 14:14:512021-05-24 14:14:51
910032-509-8940lms1발송완료<NA><NA>2021-05-24 13:57:192021-05-24 13:57:192021-05-24 13:57:19
번호발신번호메시지 종류발송건수발송상태발신부서발신자등록일발송예정일발송완료일
17751776032-509-8940sms1발송완료<NA><NA>2021-01-11 09:07:342021-01-11 09:07:342021-01-11 09:07:34
17761777032-509-8940sms1발송완료<NA><NA>2021-01-11 09:07:252021-01-11 09:07:252021-01-11 09:07:26
17771778032-509-8940sms1발송완료<NA><NA>2021-01-11 09:06:422021-01-11 09:06:422021-01-11 09:06:42
17781779032-509-8940sms1발송완료<NA><NA>2021-01-11 09:06:182021-01-11 09:06:182021-01-11 09:06:19
17791780032-509-8940sms1발송완료<NA><NA>2021-01-11 09:03:362021-01-11 09:03:362021-01-11 09:03:36
17801781032-509-8940sms1발송완료<NA><NA>2021-01-11 09:03:102021-01-11 09:03:102021-01-11 09:03:10
17811782032-509-8940sms1발송완료<NA><NA>2021-01-11 09:02:352021-01-11 09:02:352021-01-11 09:02:35
17821783032-509-8940sms1발송완료<NA><NA>2021-01-11 09:02:182021-01-11 09:02:182021-01-11 09:02:18
17831784032-509-8940sms1발송완료<NA><NA>2021-01-11 09:01:092021-01-11 09:01:092021-01-11 09:01:13
17841785032-509-8940sms1발송완료<NA><NA>2021-01-11 09:00:572021-01-11 09:00:572021-01-11 09:00:59