Overview

Dataset statistics

Number of variables7
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory65.0 B

Variable types

Categorical3
Numeric4

Dataset

Description대구광역시 남구 알리미시스템에 대한 데이터로 월별 단문(SMS), 장문(LMS), 멀티미디어(MMS) 발송현황 등에 대한 항목을 제공합니다.
Author대구광역시 남구
URLhttps://www.data.go.kr/data/15089393/fileData.do

Alerts

사용기관 has constant value ""Constant
데이터기준일자 has constant value ""Constant
단문(SMS) is highly overall correlated with 장문(LMS) and 2 other fieldsHigh correlation
장문(LMS) is highly overall correlated with 단문(SMS) and 1 other fieldsHigh correlation
멀티미디어(MMS) is highly overall correlated with 단문(SMS) and 1 other fieldsHigh correlation
연도 is highly overall correlated with 단문(SMS)High correlation
단문(SMS) has unique valuesUnique
장문(LMS) has unique valuesUnique
멀티미디어(MMS) has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:26:02.031690
Analysis finished2023-12-12 06:26:04.164224
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용기관
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
대구광역시 남구청
33 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 남구청
2nd row대구광역시 남구청
3rd row대구광역시 남구청
4th row대구광역시 남구청
5th row대구광역시 남구청

Common Values

ValueCountFrequency (%)
대구광역시 남구청 33
100.0%

Length

2023-12-12T15:26:04.252354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:26:04.356987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 33
50.0%
남구청 33
50.0%

연도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
2019
12 
2020
12 
2021
9 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 12
36.4%
2020 12
36.4%
2021 9
27.3%

Length

2023-12-12T15:26:04.459189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:26:04.590419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 12
36.4%
2020 12
36.4%
2021 9
27.3%

월
Real number (ℝ)

Distinct12
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0909091
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T15:26:04.710532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11.4
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3574882
Coefficient of variation (CV)0.55122941
Kurtosis-1.0737448
Mean6.0909091
Median Absolute Deviation (MAD)3
Skewness0.12709023
Sum201
Variance11.272727
MonotonicityNot monotonic
2023-12-12T15:26:04.869030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 3
9.1%
2 3
9.1%
3 3
9.1%
4 3
9.1%
5 3
9.1%
6 3
9.1%
7 3
9.1%
8 3
9.1%
9 3
9.1%
10 2
6.1%
Other values (2) 4
12.1%
ValueCountFrequency (%)
1 3
9.1%
2 3
9.1%
3 3
9.1%
4 3
9.1%
5 3
9.1%
6 3
9.1%
7 3
9.1%
8 3
9.1%
9 3
9.1%
10 2
6.1%
ValueCountFrequency (%)
12 2
6.1%
11 2
6.1%
10 2
6.1%
9 3
9.1%
8 3
9.1%
7 3
9.1%
6 3
9.1%
5 3
9.1%
4 3
9.1%
3 3
9.1%

단문(SMS)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42212.424
Minimum1930
Maximum116617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T15:26:05.034569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1930
5-th percentile3039.6
Q14512
median46625
Q363374
95-th percentile101202.2
Maximum116617
Range114687
Interquartile range (IQR)58862

Descriptive statistics

Standard deviation35919.736
Coefficient of variation (CV)0.85092806
Kurtosis-0.93904654
Mean42212.424
Median Absolute Deviation (MAD)37729
Skewness0.43514945
Sum1393010
Variance1.2902275 × 109
MonotonicityNot monotonic
2023-12-12T15:26:05.207162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
3278 1
 
3.0%
4512 1
 
3.0%
50001 1
 
3.0%
61702 1
 
3.0%
60456 1
 
3.0%
44846 1
 
3.0%
35380 1
 
3.0%
8896 1
 
3.0%
3980 1
 
3.0%
3483 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1930 1
3.0%
2682 1
3.0%
3278 1
3.0%
3483 1
3.0%
3938 1
3.0%
3980 1
3.0%
4046 1
3.0%
4185 1
3.0%
4512 1
3.0%
5491 1
3.0%
ValueCountFrequency (%)
116617 1
3.0%
102434 1
3.0%
100381 1
3.0%
100122 1
3.0%
95554 1
3.0%
83458 1
3.0%
65957 1
3.0%
63390 1
3.0%
63374 1
3.0%
61702 1
3.0%

장문(LMS)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4447.4242
Minimum534
Maximum19276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T15:26:05.379614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum534
5-th percentile696
Q1921
median1482
Q36396
95-th percentile14868
Maximum19276
Range18742
Interquartile range (IQR)5475

Descriptive statistics

Standard deviation5257.858
Coefficient of variation (CV)1.1822254
Kurtosis0.98409889
Mean4447.4242
Median Absolute Deviation (MAD)712
Skewness1.4443698
Sum146765
Variance27645071
MonotonicityNot monotonic
2023-12-12T15:26:05.551675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
15045 1
 
3.0%
1531 1
 
3.0%
913 1
 
3.0%
921 1
 
3.0%
1248 1
 
3.0%
988 1
 
3.0%
2196 1
 
3.0%
901 1
 
3.0%
2562 1
 
3.0%
10194 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
534 1
3.0%
585 1
3.0%
770 1
3.0%
774 1
3.0%
812 1
3.0%
882 1
3.0%
901 1
3.0%
913 1
3.0%
921 1
3.0%
988 1
3.0%
ValueCountFrequency (%)
19276 1
3.0%
15045 1
3.0%
14750 1
3.0%
13741 1
3.0%
11604 1
3.0%
10194 1
3.0%
9201 1
3.0%
8614 1
3.0%
6396 1
3.0%
5313 1
3.0%

멀티미디어(MMS)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54858.848
Minimum10874
Maximum114673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T15:26:05.730720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10874
5-th percentile22220
Q137689
median45700
Q364724
95-th percentile113357.8
Maximum114673
Range103799
Interquartile range (IQR)27035

Descriptive statistics

Standard deviation27885.686
Coefficient of variation (CV)0.508317
Kurtosis0.17446589
Mean54858.848
Median Absolute Deviation (MAD)13163
Skewness0.96383263
Sum1810342
Variance7.7761146 × 108
MonotonicityNot monotonic
2023-12-12T15:26:05.877382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
51782 1
 
3.0%
43685 1
 
3.0%
42231 1
 
3.0%
54295 1
 
3.0%
42275 1
 
3.0%
42194 1
 
3.0%
37777 1
 
3.0%
64724 1
 
3.0%
48570 1
 
3.0%
42751 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
10874 1
3.0%
20087 1
3.0%
23642 1
3.0%
27020 1
3.0%
30477 1
3.0%
32537 1
3.0%
36432 1
3.0%
36551 1
3.0%
37689 1
3.0%
37777 1
3.0%
ValueCountFrequency (%)
114673 1
3.0%
113971 1
3.0%
112949 1
3.0%
108340 1
3.0%
92304 1
3.0%
87529 1
3.0%
74459 1
3.0%
66852 1
3.0%
64724 1
3.0%
63855 1
3.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2021-09-23
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-23
2nd row2021-09-23
3rd row2021-09-23
4th row2021-09-23
5th row2021-09-23

Common Values

ValueCountFrequency (%)
2021-09-23 33
100.0%

Length

2023-12-12T15:26:06.053101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:26:06.205998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-23 33
100.0%

Interactions

2023-12-12T15:26:03.474088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.239454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.645084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.051531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.619509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.342786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.748988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.147858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.713909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.449051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.840317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.260222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.863031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.559722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:02.948897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:03.370499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:26:06.291203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월단문(SMS)장문(LMS)멀티미디어(MMS)
연도1.0000.0000.6830.4250.485
월0.0001.0000.0000.3630.000
단문(SMS)0.6830.0001.0000.0000.720
장문(LMS)0.4250.3630.0001.0000.442
멀티미디어(MMS)0.4850.0000.7200.4421.000
2023-12-12T15:26:06.432759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월단문(SMS)장문(LMS)멀티미디어(MMS)연도
월1.0000.332-0.068-0.1260.000
단문(SMS)0.3321.000-0.669-0.5210.524
장문(LMS)-0.068-0.6691.0000.6240.282
멀티미디어(MMS)-0.126-0.5210.6241.0000.270
연도0.0000.5240.2820.2701.000

Missing values

2023-12-12T15:26:03.986201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:26:04.107609image/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

사용기관연도월단문(SMS)장문(LMS)멀티미디어(MMS)데이터기준일자
0대구광역시 남구청20191327815045517822021-09-23
1대구광역시 남구청20192348310194427512021-09-23
2대구광역시 남구청2019341859201668522021-09-23
3대구광역시 남구청201943938192761146732021-09-23
4대구광역시 남구청201953780514750923042021-09-23
5대구광역시 남구청20196955541424108742021-09-23
6대구광역시 남구청20197100381770365512021-09-23
7대구광역시 남구청20198834581212200872021-09-23
8대구광역시 남구청201991166171482638552021-09-23
9대구광역시 남구청2019101024341757529662021-09-23
사용기관연도월단문(SMS)장문(LMS)멀티미디어(MMS)데이터기준일자
23대구광역시 남구청202012353802196377772021-09-23
24대구광역시 남구청202118896901647242021-09-23
25대구광역시 남구청2021245121531436852021-09-23
26대구광역시 남구청2021339802562485702021-09-23
27대구광역시 남구청2021463185313744592021-09-23
28대구광역시 남구청2021526826396617942021-09-23
29대구광역시 남구청202165491137411083402021-09-23
30대구광역시 남구청2021710234116041139712021-09-23
31대구광역시 남구청20218404686141129492021-09-23
32대구광역시 남구청2021919304842875292021-09-23