Overview

Dataset statistics

Number of variables7
Number of observations316
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.3 KiB
Average record size in memory62.4 B

Variable types

DateTime1
Numeric6

Dataset

Description공공데이터 제공 신청에 따른 2020년 포항시 코로나 일일확진자 수(남구, 북구, 총 누적)에 대한 데이터를 제공합니다
URLhttps://www.data.go.kr/data/15121131/fileData.do

Alerts

포항시 is highly overall correlated with 북구 and 1 other fieldsHigh correlation
북구 is highly overall correlated with 포항시 and 1 other fieldsHigh correlation
북구 누적수 is highly overall correlated with 남구 누적수 and 1 other fieldsHigh correlation
남구 is highly overall correlated with 포항시 and 1 other fieldsHigh correlation
남구 누적수 is highly overall correlated with 북구 누적수 and 1 other fieldsHigh correlation
포항시 누적 is highly overall correlated with 북구 누적수 and 1 other fieldsHigh correlation
일자 has unique valuesUnique
포항시 has 236 (74.7%) zerosZeros
북구 has 254 (80.4%) zerosZeros
남구 has 265 (83.9%) zerosZeros

Reproduction

Analysis started2023-12-12 12:00:37.070894
Analysis finished2023-12-12 12:00:41.824411
Duration4.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

UNIQUE 

Distinct316
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2020-02-20 00:00:00
Maximum2020-12-31 00:00:00
2023-12-12T21:00:42.280985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:42.439512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

포항시
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.78164557
Minimum0
Maximum13
Zeros236
Zeros (%)74.7%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:42.597673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum13
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8515832
Coefficient of variation (CV)2.3688271
Kurtosis14.261254
Mean0.78164557
Median Absolute Deviation (MAD)0
Skewness3.4121537
Sum247
Variance3.4283605
MonotonicityNot monotonic
2023-12-12T21:00:42.770853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 236
74.7%
1 26
 
8.2%
2 18
 
5.7%
3 11
 
3.5%
5 9
 
2.8%
4 6
 
1.9%
6 4
 
1.3%
8 2
 
0.6%
11 1
 
0.3%
12 1
 
0.3%
Other values (2) 2
 
0.6%
ValueCountFrequency (%)
0 236
74.7%
1 26
 
8.2%
2 18
 
5.7%
3 11
 
3.5%
4 6
 
1.9%
5 9
 
2.8%
6 4
 
1.3%
7 1
 
0.3%
8 2
 
0.6%
11 1
 
0.3%
ValueCountFrequency (%)
13 1
 
0.3%
12 1
 
0.3%
11 1
 
0.3%
8 2
 
0.6%
7 1
 
0.3%
6 4
 
1.3%
5 9
2.8%
4 6
 
1.9%
3 11
3.5%
2 18
5.7%

북구
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.42088608
Minimum0
Maximum9
Zeros254
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:42.912814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0735228
Coefficient of variation (CV)2.5506257
Kurtosis17.228914
Mean0.42088608
Median Absolute Deviation (MAD)0
Skewness3.6076981
Sum133
Variance1.1524513
MonotonicityNot monotonic
2023-12-12T21:00:43.049293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 254
80.4%
1 26
 
8.2%
2 19
 
6.0%
3 8
 
2.5%
5 4
 
1.3%
4 4
 
1.3%
9 1
 
0.3%
ValueCountFrequency (%)
0 254
80.4%
1 26
 
8.2%
2 19
 
6.0%
3 8
 
2.5%
4 4
 
1.3%
5 4
 
1.3%
9 1
 
0.3%
ValueCountFrequency (%)
9 1
 
0.3%
5 4
 
1.3%
4 4
 
1.3%
3 8
 
2.5%
2 19
 
6.0%
1 26
 
8.2%
0 254
80.4%

북구 누적수
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.879747
Minimum0
Maximum133
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:43.221597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile27
Q131
median31
Q366
95-th percentile109.25
Maximum133
Range133
Interquartile range (IQR)35

Descriptive statistics

Standard deviation25.779125
Coefficient of variation (CV)0.56188463
Kurtosis1.6149038
Mean45.879747
Median Absolute Deviation (MAD)1
Skewness1.4026579
Sum14498
Variance664.56327
MonotonicityIncreasing
2023-12-12T21:00:43.416905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 149
47.2%
69 28
 
8.9%
66 13
 
4.1%
35 12
 
3.8%
37 11
 
3.5%
30 8
 
2.5%
65 6
 
1.9%
38 6
 
1.9%
70 6
 
1.9%
68 5
 
1.6%
Other values (53) 72
22.8%
ValueCountFrequency (%)
0 2
0.6%
2 1
0.3%
5 2
0.6%
7 1
0.3%
9 1
0.3%
11 1
0.3%
12 1
0.3%
17 2
0.6%
18 1
0.3%
19 1
0.3%
ValueCountFrequency (%)
133 1
 
0.3%
131 2
0.6%
129 1
 
0.3%
124 1
 
0.3%
122 1
 
0.3%
120 1
 
0.3%
117 1
 
0.3%
116 1
 
0.3%
115 3
0.9%
114 2
0.6%

남구
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.36075949
Minimum0
Maximum10
Zeros265
Zeros (%)83.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:43.598443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1420858
Coefficient of variation (CV)3.1657818
Kurtosis30.231569
Mean0.36075949
Median Absolute Deviation (MAD)0
Skewness4.9594022
Sum114
Variance1.3043601
MonotonicityNot monotonic
2023-12-12T21:00:43.744042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 265
83.9%
1 25
 
7.9%
2 14
 
4.4%
3 4
 
1.3%
5 3
 
0.9%
4 2
 
0.6%
8 2
 
0.6%
10 1
 
0.3%
ValueCountFrequency (%)
0 265
83.9%
1 25
 
7.9%
2 14
 
4.4%
3 4
 
1.3%
4 2
 
0.6%
5 3
 
0.9%
8 2
 
0.6%
10 1
 
0.3%
ValueCountFrequency (%)
10 1
 
0.3%
8 2
 
0.6%
5 3
 
0.9%
4 2
 
0.6%
3 4
 
1.3%
2 14
 
4.4%
1 25
 
7.9%
0 265
83.9%

남구 누적수
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.439873
Minimum1
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:43.922139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.75
Q119
median21
Q336
95-th percentile59
Maximum114
Range113
Interquartile range (IQR)17

Descriptive statistics

Standard deviation15.677084
Coefficient of variation (CV)0.57132495
Kurtosis8.6147249
Mean27.439873
Median Absolute Deviation (MAD)2
Skewness2.5101029
Sum8671
Variance245.77098
MonotonicityIncreasing
2023-12-12T21:00:44.113814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 66
20.9%
20 46
14.6%
21 40
12.7%
36 24
 
7.6%
37 23
 
7.3%
22 13
 
4.1%
40 12
 
3.8%
18 12
 
3.8%
17 10
 
3.2%
27 6
 
1.9%
Other values (41) 64
20.3%
ValueCountFrequency (%)
1 1
 
0.3%
2 1
 
0.3%
5 1
 
0.3%
6 1
 
0.3%
8 4
1.3%
9 1
 
0.3%
10 2
0.6%
12 2
0.6%
13 1
 
0.3%
16 2
0.6%
ValueCountFrequency (%)
114 1
 
0.3%
111 1
 
0.3%
103 1
 
0.3%
98 1
 
0.3%
90 1
 
0.3%
80 1
 
0.3%
76 1
 
0.3%
71 1
 
0.3%
66 3
0.9%
64 3
0.9%

포항시 누적
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.31962
Minimum1
Maximum247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:00:44.318334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile43.75
Q150
median52
Q3102
95-th percentile168.25
Maximum247
Range246
Interquartile range (IQR)52

Descriptive statistics

Standard deviation41.099056
Coefficient of variation (CV)0.5605465
Kurtosis3.3366616
Mean73.31962
Median Absolute Deviation (MAD)4
Skewness1.7228412
Sum23169
Variance1689.1324
MonotonicityIncreasing
2023-12-12T21:00:44.520185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 66
20.9%
51 46
14.6%
52 25
 
7.9%
106 23
 
7.3%
102 13
 
4.1%
49 12
 
3.8%
59 10
 
3.2%
56 9
 
2.8%
47 8
 
2.5%
101 6
 
1.9%
Other values (70) 98
31.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
7 1
0.3%
11 1
0.3%
13 1
0.3%
15 1
0.3%
17 1
0.3%
19 1
0.3%
21 1
0.3%
27 2
0.6%
ValueCountFrequency (%)
247 1
0.3%
242 1
0.3%
234 1
0.3%
227 1
0.3%
214 1
0.3%
202 1
0.3%
196 1
0.3%
188 1
0.3%
182 1
0.3%
181 2
0.6%

Interactions

2023-12-12T21:00:40.729974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.341305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.044674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.717681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.358810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.004094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.844623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.453616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.151713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.819005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.459314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.113610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.953897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.568784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.253622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.921542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.569078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.206038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:41.079724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.693215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.374887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.038999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.668025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.309718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:41.206239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.806995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.487767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.138303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.778858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.495618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:41.347499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:37.925546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:38.609985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.243953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:39.884848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:40.617092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:00:44.663648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
포항시북구북구 누적수남구남구 누적수포항시 누적
포항시1.0000.8290.7490.8180.8160.738
북구0.8291.0000.6920.5350.6300.632
북구 누적수0.7490.6921.0000.6480.9710.977
남구0.8180.5350.6481.0000.8480.772
남구 누적수0.8160.6300.9710.8481.0000.981
포항시 누적0.7380.6320.9770.7720.9811.000
2023-12-12T21:00:44.793532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
포항시북구북구 누적수남구남구 누적수포항시 누적
포항시1.0000.8760.2750.7930.2610.262
북구0.8761.0000.2570.5180.2350.238
북구 누적수0.2750.2571.0000.2440.9460.952
남구0.7930.5180.2441.0000.2390.235
남구 누적수0.2610.2350.9460.2391.0000.999
포항시 누적0.2620.2380.9520.2350.9991.000

Missing values

2023-12-12T21:00:41.552424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:00:41.743529image/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

일자포항시북구북구 누적수남구남구 누적수포항시 누적
02020-02-20100111
12020-02-21100122
22020-02-22522357
32020-02-234351611
42020-02-242052813
52020-02-252270815
62020-02-262290817
72020-02-2722110819
82020-02-2821121921
92020-02-29651711027
일자포항시북구북구 누적수남구남구 누적수포항시 누적
3062020-12-2200115066181
3072020-12-2311116066182
3082020-12-2461117571188
3092020-12-2583120576196
3102020-12-2662122480202
3112020-12-271221241090214
3122020-12-28135129898227
3132020-12-29721315103234
3142020-12-30801318111242
3152020-12-31521333114247