Overview

Dataset statistics

Number of variables6
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory54.4 B

Variable types

Categorical2
Numeric3
DateTime1

Dataset

Description경기도 포천시 문자전송시스템에서 제공하는 문자메시지사용현황(연도별, 업무구분, SMS사용건수, LMS사용건수, MMS사용건수) 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15061978/fileData.do

Alerts

데이터기준일 has constant value ""Constant
LMS사용건수 is highly overall correlated with MMS사용건수High correlation
MMS사용건수 is highly overall correlated with LMS사용건수High correlation
SMS사용건수 has unique valuesUnique
LMS사용건수 has 7 (12.7%) zerosZeros
MMS사용건수 has 18 (32.7%) zerosZeros

Reproduction

Analysis started2023-12-12 23:05:26.405524
Analysis finished2023-12-12 23:05:28.024348
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct4
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
2020
16 
2017
13 
2018
13 
2019
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2020 16
29.1%
2017 13
23.6%
2018 13
23.6%
2019 13
23.6%

Length

2023-12-13T08:05:28.103179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:28.218290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 16
29.1%
2017 13
23.6%
2018 13
23.6%
2019 13
23.6%

업무구분
Categorical

Distinct18
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Memory size572.0 B
민원통보안내
4 
단체장관리
4 
일반업무
4 
회의안내
4 
세금안내
4 
Other values (13)
35 

Length

Max length13
Median length4
Mean length4.6727273
Min length2

Unique

Unique5 ?
Unique (%)9.1%

Sample

1st row민원통보안내
2nd row세금안내
3rd row회의안내
4th row교육안내
5th row당직업무관리

Common Values

ValueCountFrequency (%)
민원통보안내 4
 
7.3%
단체장관리 4
 
7.3%
일반업무 4
 
7.3%
회의안내 4
 
7.3%
세금안내 4
 
7.3%
행정홍보 4
 
7.3%
도서대여 4
 
7.3%
직원관리 4
 
7.3%
기타 4
 
7.3%
당직업무관리 4
 
7.3%
Other values (8) 15
27.3%

Length

2023-12-13T08:05:28.345788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
민원통보안내 4
 
7.3%
도서대여 4
 
7.3%
교육안내 4
 
7.3%
단체장관리 4
 
7.3%
기타 4
 
7.3%
직원관리 4
 
7.3%
당직업무관리 4
 
7.3%
행정홍보 4
 
7.3%
세금안내 4
 
7.3%
회의안내 4
 
7.3%
Other values (8) 15
27.3%

SMS사용건수
Real number (ℝ)

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23539.764
Minimum31
Maximum120700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-13T08:05:28.498224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile179.6
Q12951
median12623
Q330432.5
95-th percentile92764.1
Maximum120700
Range120669
Interquartile range (IQR)27481.5

Descriptive statistics

Standard deviation29706.683
Coefficient of variation (CV)1.2619788
Kurtosis3.0813886
Mean23539.764
Median Absolute Deviation (MAD)11441
Skewness1.8731348
Sum1294687
Variance8.8248703 × 108
MonotonicityNot monotonic
2023-12-13T08:05:28.666139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7921 1
 
1.8%
229 1
 
1.8%
1300 1
 
1.8%
11805 1
 
1.8%
304 1
 
1.8%
35531 1
 
1.8%
114897 1
 
1.8%
12700 1
 
1.8%
262 1
 
1.8%
21569 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
31 1
1.8%
75 1
1.8%
97 1
1.8%
215 1
1.8%
229 1
1.8%
262 1
1.8%
304 1
1.8%
324 1
1.8%
404 1
1.8%
405 1
1.8%
ValueCountFrequency (%)
120700 1
1.8%
114897 1
1.8%
99237 1
1.8%
89990 1
1.8%
86871 1
1.8%
55190 1
1.8%
52930 1
1.8%
52673 1
1.8%
49344 1
1.8%
48836 1
1.8%

LMS사용건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15776.673
Minimum0
Maximum87146
Zeros7
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-13T08:05:28.842129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1904
median8460
Q323360.5
95-th percentile55321.5
Maximum87146
Range87146
Interquartile range (IQR)22456.5

Descriptive statistics

Standard deviation19210.808
Coefficient of variation (CV)1.2176717
Kurtosis3.0182238
Mean15776.673
Median Absolute Deviation (MAD)8155
Skewness1.7166726
Sum867717
Variance3.6905514 × 108
MonotonicityNot monotonic
2023-12-13T08:05:29.027353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 7
 
12.7%
65485 1
 
1.8%
15295 1
 
1.8%
7400 1
 
1.8%
59938 1
 
1.8%
6399 1
 
1.8%
3005 1
 
1.8%
35418 1
 
1.8%
24240 1
 
1.8%
1157 1
 
1.8%
Other values (39) 39
70.9%
ValueCountFrequency (%)
0 7
12.7%
37 1
 
1.8%
148 1
 
1.8%
288 1
 
1.8%
305 1
 
1.8%
542 1
 
1.8%
625 1
 
1.8%
651 1
 
1.8%
1157 1
 
1.8%
1830 1
 
1.8%
ValueCountFrequency (%)
87146 1
1.8%
65485 1
1.8%
59938 1
1.8%
53343 1
1.8%
43954 1
1.8%
43178 1
1.8%
35418 1
1.8%
35267 1
1.8%
34109 1
1.8%
33604 1
1.8%

MMS사용건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.27273
Minimum0
Maximum1254
Zeros18
Zeros (%)32.7%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-13T08:05:29.184024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q3124.5
95-th percentile532.4
Maximum1254
Range1254
Interquartile range (IQR)124.5

Descriptive statistics

Standard deviation246.60416
Coefficient of variation (CV)2.1770832
Kurtosis11.058416
Mean113.27273
Median Absolute Deviation (MAD)4
Skewness3.1926952
Sum6230
Variance60813.609
MonotonicityNot monotonic
2023-12-13T08:05:29.351921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 18
32.7%
1 5
 
9.1%
3 3
 
5.5%
84 2
 
3.6%
289 1
 
1.8%
518 1
 
1.8%
5 1
 
1.8%
18 1
 
1.8%
132 1
 
1.8%
348 1
 
1.8%
Other values (21) 21
38.2%
ValueCountFrequency (%)
0 18
32.7%
1 5
 
9.1%
2 1
 
1.8%
3 3
 
5.5%
4 1
 
1.8%
5 1
 
1.8%
8 1
 
1.8%
10 1
 
1.8%
14 1
 
1.8%
18 1
 
1.8%
ValueCountFrequency (%)
1254 1
1.8%
1042 1
1.8%
566 1
1.8%
518 1
1.8%
507 1
1.8%
364 1
1.8%
348 1
1.8%
289 1
1.8%
152 1
1.8%
149 1
1.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2023-12-13T08:05:29.473597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:29.584926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:05:27.207891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.633355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.931797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.306428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.730152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.032998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.397533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.825153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.115867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:05:29.676634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도업무구분SMS사용건수LMS사용건수MMS사용건수
연도1.0000.0000.0000.2450.125
업무구분0.0001.0000.6830.8180.000
SMS사용건수0.0000.6831.0000.5790.081
LMS사용건수0.2450.8180.5791.0000.776
MMS사용건수0.1250.0000.0810.7761.000
2023-12-13T08:05:29.807194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무구분연도
업무구분1.0000.000
연도0.0001.000
2023-12-13T08:05:29.924501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SMS사용건수LMS사용건수MMS사용건수연도업무구분
SMS사용건수1.0000.4200.3210.0000.334
LMS사용건수0.4201.0000.7980.1410.371
MMS사용건수0.3210.7981.0000.0670.000
연도0.0000.1410.0671.0000.000
업무구분0.3340.3710.0000.0001.000

Missing values

2023-12-13T08:05:27.854535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:05:27.977179image/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

연도업무구분SMS사용건수LMS사용건수MMS사용건수데이터기준일
02017민원통보안내79217905302021-08-31
12017세금안내22930512021-08-31
22017회의안내1262310532442021-08-31
32017교육안내6880789512021-08-31
42017당직업무관리3424497302021-08-31
52017기타18913438502021-08-31
62017직원관리243853133712542021-08-31
72017단체장관리2127183042021-08-31
82017행정홍보19829299751312021-08-31
92017재난관리868712226222021-08-31
연도업무구분SMS사용건수LMS사용건수MMS사용건수데이터기준일
452020가상계좌시스템2478002021-08-31
462020당직업무관리4122623812021-08-31
472020행정홍보52673302352892021-08-31
482020기타27968439541262021-08-31
492020세금안내185514802021-08-31
502020단체장관리215662002021-08-31
512020직원관리15033914012021-08-31
522020주민등록시군구정보시스템11810002021-08-31
532020포천시ARS과오납환부안내24064002021-08-31
542020푸른물시스템32897002021-08-31