Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory57.9 B

Variable types

Text1
Numeric5

Dataset

Description사립학교교직원연금공단 SNS 구독자 현황과 관련된 데이터로 월별 SNS별(유튜브, 인스타그램, 페이스북, 블로그, 카카오) 구독자 현황 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15102553/fileData.do

Alerts

유튜브(명) is highly overall correlated with 인스타그램(명) and 3 other fieldsHigh correlation
인스타그램(명) is highly overall correlated with 유튜브(명) and 3 other fieldsHigh correlation
페이스북(명) is highly overall correlated with 유튜브(명) and 3 other fieldsHigh correlation
블로그(명) is highly overall correlated with 유튜브(명) and 3 other fieldsHigh correlation
카카오(명) is highly overall correlated with 유튜브(명) and 3 other fieldsHigh correlation
년월 has unique valuesUnique
유튜브(명) has unique valuesUnique
카카오(명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:04:12.246515
Analysis finished2023-12-12 03:04:15.732215
Duration3.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:04:15.922390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters270
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row="2021-03"
2nd row="2021-04"
3rd row="2021-05"
4th row="2021-06"
5th row="2021-07"
ValueCountFrequency (%)
2021-03 1
 
3.7%
2022-05 1
 
3.7%
2023-04 1
 
3.7%
2023-03 1
 
3.7%
2023-02 1
 
3.7%
2023-01 1
 
3.7%
2022-12 1
 
3.7%
2022-11 1
 
3.7%
2022-10 1
 
3.7%
2022-09 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T12:04:16.361216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 70
25.9%
" 54
20.0%
0 50
18.5%
= 27
 
10.0%
- 27
 
10.0%
1 20
 
7.4%
3 8
 
3.0%
4 3
 
1.1%
5 3
 
1.1%
6 2
 
0.7%
Other values (3) 6
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
60.0%
Other Punctuation 54
 
20.0%
Math Symbol 27
 
10.0%
Dash Punctuation 27
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 70
43.2%
0 50
30.9%
1 20
 
12.3%
3 8
 
4.9%
4 3
 
1.9%
5 3
 
1.9%
6 2
 
1.2%
7 2
 
1.2%
8 2
 
1.2%
9 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
" 54
100.0%
Math Symbol
ValueCountFrequency (%)
= 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 270
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 70
25.9%
" 54
20.0%
0 50
18.5%
= 27
 
10.0%
- 27
 
10.0%
1 20
 
7.4%
3 8
 
3.0%
4 3
 
1.1%
5 3
 
1.1%
6 2
 
0.7%
Other values (3) 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 70
25.9%
" 54
20.0%
0 50
18.5%
= 27
 
10.0%
- 27
 
10.0%
1 20
 
7.4%
3 8
 
3.0%
4 3
 
1.1%
5 3
 
1.1%
6 2
 
0.7%
Other values (3) 6
 
2.2%

유튜브(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6202.4074
Minimum5095
Maximum7068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:04:16.529124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5095
5-th percentile5102
Q15780
median6122
Q36772
95-th percentile7062.7
Maximum7068
Range1973
Interquartile range (IQR)992

Descriptive statistics

Standard deviation661.72126
Coefficient of variation (CV)0.10668781
Kurtosis-1.0280173
Mean6202.4074
Median Absolute Deviation (MAD)453
Skewness-0.22325296
Sum167465
Variance437875.02
MonotonicityNot monotonic
2023-12-12T12:04:16.689478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
5147 1
 
3.7%
5109 1
 
3.7%
7055 1
 
3.7%
7068 1
 
3.7%
7066 1
 
3.7%
7042 1
 
3.7%
7038 1
 
3.7%
6972 1
 
3.7%
6962 1
 
3.7%
6582 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
5095 1
3.7%
5099 1
3.7%
5109 1
3.7%
5147 1
3.7%
5652 1
3.7%
5669 1
3.7%
5721 1
3.7%
5839 1
3.7%
5890 1
3.7%
5937 1
3.7%
ValueCountFrequency (%)
7068 1
3.7%
7066 1
3.7%
7055 1
3.7%
7042 1
3.7%
7038 1
3.7%
6972 1
3.7%
6962 1
3.7%
6582 1
3.7%
6572 1
3.7%
6557 1
3.7%

인스타그램(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16450.852
Minimum10659
Maximum142464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:04:16.868015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10659
5-th percentile10664.6
Q111223.5
median11523
Q312453
95-th percentile12523.7
Maximum142464
Range131805
Interquartile range (IQR)1229.5

Descriptive statistics

Standard deviation25192.628
Coefficient of variation (CV)1.5313875
Kurtosis26.958505
Mean16450.852
Median Absolute Deviation (MAD)805
Skewness5.1903779
Sum444173
Variance6.3466853 × 108
MonotonicityNot monotonic
2023-12-12T12:04:17.063395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
11547 2
 
7.4%
10664 1
 
3.7%
11478 1
 
3.7%
12451 1
 
3.7%
12455 1
 
3.7%
12499 1
 
3.7%
12509 1
 
3.7%
12530 1
 
3.7%
12472 1
 
3.7%
12489 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
10659 1
3.7%
10664 1
3.7%
10666 1
3.7%
10675 1
3.7%
10718 1
3.7%
10902 1
3.7%
11016 1
3.7%
11431 1
3.7%
11439 1
3.7%
11458 1
3.7%
ValueCountFrequency (%)
142464 1
3.7%
12530 1
3.7%
12509 1
3.7%
12499 1
3.7%
12489 1
3.7%
12472 1
3.7%
12455 1
3.7%
12451 1
3.7%
12357 1
3.7%
11721 1
3.7%

페이스북(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5473.3333
Minimum5367
Maximum5636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:04:17.205399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5367
5-th percentile5368.2
Q15391.5
median5423
Q35599.5
95-th percentile5633
Maximum5636
Range269
Interquartile range (IQR)208

Descriptive statistics

Standard deviation104.48298
Coefficient of variation (CV)0.01908946
Kurtosis-1.3231396
Mean5473.3333
Median Absolute Deviation (MAD)46
Skewness0.69724217
Sum147780
Variance10916.692
MonotonicityNot monotonic
2023-12-12T12:04:17.344060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
5633 2
 
7.4%
5367 2
 
7.4%
5394 1
 
3.7%
5430 1
 
3.7%
5632 1
 
3.7%
5636 1
 
3.7%
5628 1
 
3.7%
5626 1
 
3.7%
5607 1
 
3.7%
5592 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
5367 2
7.4%
5371 1
3.7%
5377 1
3.7%
5379 1
3.7%
5382 1
3.7%
5389 1
3.7%
5394 1
3.7%
5399 1
3.7%
5405 1
3.7%
5412 1
3.7%
ValueCountFrequency (%)
5636 1
3.7%
5633 2
7.4%
5632 1
3.7%
5628 1
3.7%
5626 1
3.7%
5607 1
3.7%
5592 1
3.7%
5514 1
3.7%
5478 1
3.7%
5438 1
3.7%

블로그(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2146.3704
Minimum429
Maximum3375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:04:17.484167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum429
5-th percentile765
Q11104.5
median2415
Q33155
95-th percentile3372
Maximum3375
Range2946
Interquartile range (IQR)2050.5

Descriptive statistics

Standard deviation1012.6556
Coefficient of variation (CV)0.4717991
Kurtosis-1.5546352
Mean2146.3704
Median Absolute Deviation (MAD)952
Skewness-0.14070484
Sum57952
Variance1025471.4
MonotonicityNot monotonic
2023-12-12T12:04:17.619922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3372 2
 
7.4%
429 1
 
3.7%
2423 1
 
3.7%
3375 1
 
3.7%
3367 1
 
3.7%
3370 1
 
3.7%
3252 1
 
3.7%
3210 1
 
3.7%
3100 1
 
3.7%
3088 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
429 1
3.7%
744 1
3.7%
814 1
3.7%
973 1
3.7%
999 1
3.7%
1053 1
3.7%
1090 1
3.7%
1119 1
3.7%
1429 1
3.7%
1561 1
3.7%
ValueCountFrequency (%)
3375 1
3.7%
3372 2
7.4%
3370 1
3.7%
3367 1
3.7%
3252 1
3.7%
3210 1
3.7%
3100 1
3.7%
3088 1
3.7%
2916 1
3.7%
2544 1
3.7%

카카오(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41088.593
Minimum26598
Maximum58412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:04:17.772990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26598
5-th percentile27728.3
Q131519.5
median37790
Q355587.5
95-th percentile57718.7
Maximum58412
Range31814
Interquartile range (IQR)24068

Descriptive statistics

Standard deviation11217.861
Coefficient of variation (CV)0.27301642
Kurtosis-1.3026629
Mean41088.593
Median Absolute Deviation (MAD)7085
Skewness0.50365353
Sum1109392
Variance1.258404 × 108
MonotonicityStrictly increasing
2023-12-12T12:04:17.939703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
26598 1
 
3.7%
27479 1
 
3.7%
58412 1
 
3.7%
57914 1
 
3.7%
57263 1
 
3.7%
57000 1
 
3.7%
56523 1
 
3.7%
56389 1
 
3.7%
55831 1
 
3.7%
55344 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
26598 1
3.7%
27479 1
3.7%
28310 1
3.7%
28888 1
3.7%
29631 1
3.7%
30705 1
3.7%
31284 1
3.7%
31755 1
3.7%
35716 1
3.7%
35984 1
3.7%
ValueCountFrequency (%)
58412 1
3.7%
57914 1
3.7%
57263 1
3.7%
57000 1
3.7%
56523 1
3.7%
56389 1
3.7%
55831 1
3.7%
55344 1
3.7%
43931 1
3.7%
40121 1
3.7%

Interactions

2023-12-12T12:04:15.002711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:12.492205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.108476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.661882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.522518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:15.099985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:12.606211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.248143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.134325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.626485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:15.209588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:12.725153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.349868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.222315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.718516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:15.289366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:12.852852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.445605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.299893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.806419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:15.385157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:12.982609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:13.548540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.419981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:04:14.915761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:04:18.040667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월유튜브(명)인스타그램(명)페이스북(명)블로그(명)카카오(명)
년월1.0001.0001.0001.0001.0001.000
유튜브(명)1.0001.0000.0000.8610.9430.840
인스타그램(명)1.0000.0001.0000.5140.0000.000
페이스북(명)1.0000.8610.5141.0000.7840.937
블로그(명)1.0000.9430.0000.7841.0000.934
카카오(명)1.0000.8400.0000.9370.9341.000
2023-12-12T12:04:18.162961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유튜브(명)인스타그램(명)페이스북(명)블로그(명)카카오(명)
유튜브(명)1.0000.8750.9310.9850.990
인스타그램(명)0.8751.0000.7820.8870.883
페이스북(명)0.9310.7821.0000.9230.928
블로그(명)0.9850.8870.9231.0000.997
카카오(명)0.9900.8830.9280.9971.000

Missing values

2023-12-12T12:04:15.538283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:04:15.671397image/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

년월유튜브(명)인스타그램(명)페이스북(명)블로그(명)카카오(명)
0="2021-03"514710664539442926598
1="2021-04"510910659539974427479
2="2021-05"509510666538981428310
3="2021-06"509910675538297328888
4="2021-07"566910718537799929631
5="2021-08"5652109025371105330705
6="2021-09"5721110165367109031284
7="2021-10"5839115475367111931755
8="2021-11"5890115475379142935716
9="2021-12"5937115675405156135984
년월유튜브(명)인스타그램(명)페이스북(명)블로그(명)카카오(명)
17="2022-08"6546117215478291640121
18="2022-09"6557123575514308843931
19="2022-10"65821424645592310055344
20="2022-11"6962124895607321055831
21="2022-12"6972124725626325256389
22="2023-01"7038125305628337256523
23="2023-02"7042125095633337057000
24="2023-03"7066124995636336757263
25="2023-04"7068124555632337257914
26="2023-05"7055124515633337558412