Overview

Dataset statistics

Number of variables18
Number of observations181
Missing cells596
Missing cells (%)18.3%
Duplicate rows9
Duplicate rows (%)5.0%
Total size in memory28.6 KiB
Average record size in memory161.7 B

Variable types

Text1
Numeric8
Categorical9

Dataset

Description2014-2019년 문예진흥기금 공모사업 중 문학 분야 "문예지발간" 지원 사업의 전자책/웹진 문예지 보급현황(예: 판매부수, 정기구독수, 누적방문수 등)
Author한국문화예술위원회
URLhttps://www.data.go.kr/data/15076436/fileData.do

Alerts

Dataset has 9 (5.0%) duplicate rowsDuplicates
웹진_연간방문자수_추세1년전(명) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
웹진_연간방문자수_추세3년전(명) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 3 other fieldsHigh correlation
전자책_정기구독_실적(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 10 other fieldsHigh correlation
전자책_단권판매_추세1년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 11 other fieldsHigh correlation
전자책_정기구독_추세1년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_정기구독_추세3년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 3 other fieldsHigh correlation
전자책_정기구독_추세2년전(부) is highly overall correlated with 사업연도 and 15 other fieldsHigh correlation
웹진_연간방문자수_실적(명) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
웹진_연간방문자수_추세2년전(명) is highly overall correlated with 사업연도 and 15 other fieldsHigh correlation
사업연도 is highly overall correlated with 전자책_정기구독_추세2년전(부) and 1 other fieldsHigh correlation
전자책_단권판매_추세3년전(부) is highly overall correlated with 전자책_단권판매_추세2년전(부) and 14 other fieldsHigh correlation
전자책_단권판매_추세2년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_단권판매_실적(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_총판매부수_추세3년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 13 other fieldsHigh correlation
전자책_총판매부수_추세2년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_총판매부수_추세1년전(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_총판매부수_실적(부) is highly overall correlated with 전자책_단권판매_추세3년전(부) and 12 other fieldsHigh correlation
전자책_단권판매_추세1년전(부) is highly imbalanced (53.3%)Imbalance
웹진_연간방문자수_실적(명) is highly imbalanced (51.3%)Imbalance
전자책_단권판매_추세3년전(부) has 84 (46.4%) missing valuesMissing
전자책_단권판매_추세2년전(부) has 84 (46.4%) missing valuesMissing
전자책_단권판매_실적(부) has 84 (46.4%) missing valuesMissing
전자책_총판매부수_추세3년전(부) has 86 (47.5%) missing valuesMissing
전자책_총판매부수_추세2년전(부) has 86 (47.5%) missing valuesMissing
전자책_총판매부수_추세1년전(부) has 86 (47.5%) missing valuesMissing
전자책_총판매부수_실적(부) has 86 (47.5%) missing valuesMissing
전자책_단권판매_추세3년전(부) has 91 (50.3%) zerosZeros
전자책_단권판매_추세2년전(부) has 92 (50.8%) zerosZeros
전자책_단권판매_실적(부) has 91 (50.3%) zerosZeros
전자책_총판매부수_추세3년전(부) has 89 (49.2%) zerosZeros
전자책_총판매부수_추세2년전(부) has 90 (49.7%) zerosZeros
전자책_총판매부수_추세1년전(부) has 90 (49.7%) zerosZeros
전자책_총판매부수_실적(부) has 89 (49.2%) zerosZeros

Reproduction

Analysis started2023-12-12 03:03:50.333422
Analysis finished2023-12-12 03:04:00.308692
Duration9.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문학단체명
Text

Distinct62
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:04:00.503164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters905
Distinct characters68
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)10.5%

Sample

1st row*제**부
2nd row*국**회
3rd row*1**학
4th row*학**네
5th row*학**상
ValueCountFrequency (%)
국**회 45
24.9%
대**학 8
 
4.4%
제**부 5
 
2.8%
학**네 4
 
2.2%
학**상 4
 
2.2%
비**비 4
 
2.2%
학**사 4
 
2.2%
음**음 4
 
2.2%
년**작 3
 
1.7%
학**당 3
 
1.7%
Other values (52) 97
53.6%
2023-12-12T12:04:01.021464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 543
60.0%
국 54
 
6.0%
회 48
 
5.3%
학 41
 
4.5%
사 17
 
1.9%
음 11
 
1.2%
대 10
 
1.1%
시 9
 
1.0%
서 9
 
1.0%
비 8
 
0.9%
Other values (58) 155
 
17.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 543
60.0%
Other Letter 360
39.8%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%
Other Punctuation
ValueCountFrequency (%)
* 543
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 545
60.2%
Hangul 360
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%
Common
ValueCountFrequency (%)
* 543
99.6%
1 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
60.2%
Hangul 360
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 543
99.6%
1 2
 
0.4%
Hangul
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%

사업연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.7624
Minimum2014
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:01.208152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12014
median2018
Q32019
95-th percentile2019
Maximum2019
Range5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.0395867
Coefficient of variation (CV)0.0010113173
Kurtosis-1.5893876
Mean2016.7624
Median Absolute Deviation (MAD)1
Skewness-0.35284142
Sum365034
Variance4.1599141
MonotonicityIncreasing
2023-12-12T12:04:01.381973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2014 51
28.2%
2018 50
27.6%
2019 47
26.0%
2015 14
 
7.7%
2017 13
 
7.2%
2016 6
 
3.3%
ValueCountFrequency (%)
2014 51
28.2%
2015 14
 
7.7%
2016 6
 
3.3%
2017 13
 
7.2%
2018 50
27.6%
2019 47
26.0%
ValueCountFrequency (%)
2019 47
26.0%
2018 50
27.6%
2017 13
 
7.2%
2016 6
 
3.3%
2015 14
 
7.7%
2014 51
28.2%

전자책_단권판매_추세3년전(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)7.2%
Missing84
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean17.298969
Minimum0
Maximum664
Zeros91
Zeros (%)50.3%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:01.543454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile69.2
Maximum664
Range664
Interquartile range (IQR)0

Descriptive statistics

Standard deviation82.898553
Coefficient of variation (CV)4.7921094
Kurtosis41.092321
Mean17.298969
Median Absolute Deviation (MAD)0
Skewness6.0203013
Sum1678
Variance6872.1701
MonotonicityNot monotonic
2023-12-12T12:04:01.681074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 91
50.3%
300 1
 
0.6%
280 1
 
0.6%
208 1
 
0.6%
664 1
 
0.6%
40 1
 
0.6%
186 1
 
0.6%
(Missing) 84
46.4%
ValueCountFrequency (%)
0 91
50.3%
40 1
 
0.6%
186 1
 
0.6%
208 1
 
0.6%
280 1
 
0.6%
300 1
 
0.6%
664 1
 
0.6%
ValueCountFrequency (%)
664 1
 
0.6%
300 1
 
0.6%
280 1
 
0.6%
208 1
 
0.6%
186 1
 
0.6%
40 1
 
0.6%
0 91
50.3%

전자책_단권판매_추세2년전(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)6.2%
Missing84
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean20.154639
Minimum0
Maximum888
Zeros92
Zeros (%)50.8%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:01.851599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum888
Range888
Interquartile range (IQR)0

Descriptive statistics

Standard deviation114.45353
Coefficient of variation (CV)5.6787687
Kurtosis44.751565
Mean20.154639
Median Absolute Deviation (MAD)0
Skewness6.5845851
Sum1955
Variance13099.611
MonotonicityNot monotonic
2023-12-12T12:04:01.985290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 92
50.8%
664 1
 
0.6%
186 1
 
0.6%
888 1
 
0.6%
40 1
 
0.6%
177 1
 
0.6%
(Missing) 84
46.4%
ValueCountFrequency (%)
0 92
50.8%
40 1
 
0.6%
177 1
 
0.6%
186 1
 
0.6%
664 1
 
0.6%
888 1
 
0.6%
ValueCountFrequency (%)
888 1
 
0.6%
664 1
 
0.6%
186 1
 
0.6%
177 1
 
0.6%
40 1
 
0.6%
0 92
50.8%

전자책_단권판매_추세1년전(부)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
92 
<NA>
84 
220
 
2
888
 
1
772
 
1

Length

Max length4
Median length1
Mean length2.441989
Min length1

Unique

Unique3 ?
Unique (%)1.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 92
50.8%
<NA> 84
46.4%
220 2
 
1.1%
888 1
 
0.6%
772 1
 
0.6%
40 1
 
0.6%

Length

2023-12-12T12:04:02.155148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:02.346561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 92
50.8%
na 84
46.4%
220 2
 
1.1%
888 1
 
0.6%
772 1
 
0.6%
40 1
 
0.6%

전자책_단권판매_실적(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)6.2%
Missing84
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean23.494845
Minimum0
Maximum772
Zeros91
Zeros (%)50.3%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:02.486950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile50
Maximum772
Range772
Interquartile range (IQR)0

Descriptive statistics

Standard deviation119.65307
Coefficient of variation (CV)5.092737
Kurtosis31.654445
Mean23.494845
Median Absolute Deviation (MAD)0
Skewness5.6208117
Sum2279
Variance14316.857
MonotonicityNot monotonic
2023-12-12T12:04:02.635124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 91
50.3%
50 2
 
1.1%
772 1
 
0.6%
177 1
 
0.6%
755 1
 
0.6%
475 1
 
0.6%
(Missing) 84
46.4%
ValueCountFrequency (%)
0 91
50.3%
50 2
 
1.1%
177 1
 
0.6%
475 1
 
0.6%
755 1
 
0.6%
772 1
 
0.6%
ValueCountFrequency (%)
772 1
 
0.6%
755 1
 
0.6%
475 1
 
0.6%
177 1
 
0.6%
50 2
 
1.1%
0 91
50.3%

전자책_정기구독_추세3년전(부)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
96 
<NA>
84 
800
 
1

Length

Max length4
Median length1
Mean length2.4033149
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 96
53.0%
<NA> 84
46.4%
800 1
 
0.6%

Length

2023-12-12T12:04:02.820627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:02.955180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
53.0%
na 84
46.4%
800 1
 
0.6%

전자책_정기구독_추세2년전(부)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
97 
<NA>
84 

Length

Max length4
Median length1
Mean length2.3922652
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 97
53.6%
<NA> 84
46.4%

Length

2023-12-12T12:04:03.090171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:03.250843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 97
53.6%
na 84
46.4%

전자책_정기구독_추세1년전(부)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
96 
<NA>
84 
3665
 
1

Length

Max length4
Median length1
Mean length2.4088398
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 96
53.0%
<NA> 84
46.4%
3665 1
 
0.6%

Length

2023-12-12T12:04:03.395807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:03.534158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
53.0%
na 84
46.4%
3665 1
 
0.6%

전자책_정기구독_실적(부)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
93 
<NA>
86 
6392
 
1
100
 
1

Length

Max length4
Median length1
Mean length2.4530387
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 93
51.4%
<NA> 86
47.5%
6392 1
 
0.6%
100 1
 
0.6%

Length

2023-12-12T12:04:03.667048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:03.799927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 93
51.4%
na 86
47.5%
6392 1
 
0.6%
100 1
 
0.6%

전자책_총판매부수_추세3년전(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)7.4%
Missing86
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean26.084211
Minimum0
Maximum1100
Zeros89
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:03.951145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile83.8
Maximum1100
Range1100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation136.21476
Coefficient of variation (CV)5.2221155
Kurtosis46.362912
Mean26.084211
Median Absolute Deviation (MAD)0
Skewness6.5486335
Sum2478
Variance18554.461
MonotonicityNot monotonic
2023-12-12T12:04:04.085797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 89
49.2%
1100 1
 
0.6%
280 1
 
0.6%
208 1
 
0.6%
664 1
 
0.6%
40 1
 
0.6%
186 1
 
0.6%
(Missing) 86
47.5%
ValueCountFrequency (%)
0 89
49.2%
40 1
 
0.6%
186 1
 
0.6%
208 1
 
0.6%
280 1
 
0.6%
664 1
 
0.6%
1100 1
 
0.6%
ValueCountFrequency (%)
1100 1
 
0.6%
664 1
 
0.6%
280 1
 
0.6%
208 1
 
0.6%
186 1
 
0.6%
40 1
 
0.6%
0 89
49.2%

전자책_총판매부수_추세2년전(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)6.3%
Missing86
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean33.810526
Minimum0
Maximum1434
Zeros90
Zeros (%)49.7%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:04.226431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum1434
Range1434
Interquartile range (IQR)0

Descriptive statistics

Standard deviation184.89193
Coefficient of variation (CV)5.4684725
Kurtosis40.901227
Mean33.810526
Median Absolute Deviation (MAD)0
Skewness6.2217073
Sum3212
Variance34185.028
MonotonicityNot monotonic
2023-12-12T12:04:04.379379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 90
49.7%
664 1
 
0.6%
186 1
 
0.6%
888 1
 
0.6%
40 1
 
0.6%
1434 1
 
0.6%
(Missing) 86
47.5%
ValueCountFrequency (%)
0 90
49.7%
40 1
 
0.6%
186 1
 
0.6%
664 1
 
0.6%
888 1
 
0.6%
1434 1
 
0.6%
ValueCountFrequency (%)
1434 1
 
0.6%
888 1
 
0.6%
664 1
 
0.6%
186 1
 
0.6%
40 1
 
0.6%
0 90
49.7%

전자책_총판매부수_추세1년전(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)6.3%
Missing86
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean61.105263
Minimum0
Maximum3885
Zeros90
Zeros (%)49.7%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:04.545911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum3885
Range3885
Interquartile range (IQR)0

Descriptive statistics

Standard deviation414.79342
Coefficient of variation (CV)6.7881783
Kurtosis79.081088
Mean61.105263
Median Absolute Deviation (MAD)0
Skewness8.652308
Sum5805
Variance172053.58
MonotonicityNot monotonic
2023-12-12T12:04:04.701293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 90
49.7%
888 1
 
0.6%
220 1
 
0.6%
772 1
 
0.6%
40 1
 
0.6%
3885 1
 
0.6%
(Missing) 86
47.5%
ValueCountFrequency (%)
0 90
49.7%
40 1
 
0.6%
220 1
 
0.6%
772 1
 
0.6%
888 1
 
0.6%
3885 1
 
0.6%
ValueCountFrequency (%)
3885 1
 
0.6%
888 1
 
0.6%
772 1
 
0.6%
220 1
 
0.6%
40 1
 
0.6%
0 90
49.7%

전자책_총판매부수_실적(부)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)7.4%
Missing86
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean92.326316
Minimum0
Maximum6867
Zeros89
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:04:04.872841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile80
Maximum6867
Range6867
Interquartile range (IQR)0

Descriptive statistics

Standard deviation711.36842
Coefficient of variation (CV)7.7049367
Kurtosis90.196422
Mean92.326316
Median Absolute Deviation (MAD)0
Skewness9.4024654
Sum8771
Variance506045.03
MonotonicityNot monotonic
2023-12-12T12:04:05.001457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 89
49.2%
772 1
 
0.6%
177 1
 
0.6%
755 1
 
0.6%
50 1
 
0.6%
6867 1
 
0.6%
150 1
 
0.6%
(Missing) 86
47.5%
ValueCountFrequency (%)
0 89
49.2%
50 1
 
0.6%
150 1
 
0.6%
177 1
 
0.6%
755 1
 
0.6%
772 1
 
0.6%
6867 1
 
0.6%
ValueCountFrequency (%)
6867 1
 
0.6%
772 1
 
0.6%
755 1
 
0.6%
177 1
 
0.6%
150 1
 
0.6%
50 1
 
0.6%
0 89
49.2%

웹진_연간방문자수_추세3년전(명)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
94 
<NA>
86 
100000
 
1

Length

Max length6
Median length1
Mean length2.4530387
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 94
51.9%
<NA> 86
47.5%
100000 1
 
0.6%

Length

2023-12-12T12:04:05.156895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:05.285019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 94
51.9%
na 86
47.5%
100000 1
 
0.6%

웹진_연간방문자수_추세2년전(명)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
95 
<NA>
86 

Length

Max length4
Median length1
Mean length2.4254144
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 95
52.5%
<NA> 86
47.5%

Length

2023-12-12T12:04:05.452197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:05.609847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 95
52.5%
na 86
47.5%

웹진_연간방문자수_추세1년전(명)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
93 
<NA>
86 
59021
 
1
248909
 
1

Length

Max length6
Median length1
Mean length2.4751381
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 93
51.4%
<NA> 86
47.5%
59021 1
 
0.6%
248909 1
 
0.6%

Length

2023-12-12T12:04:05.736888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:05.887197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 93
51.4%
na 86
47.5%
59021 1
 
0.6%
248909 1
 
0.6%

웹진_연간방문자수_실적(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
92 
<NA>
86 
183025
 
1
206963
 
1
600
 
1

Length

Max length6
Median length1
Mean length2.4917127
Min length1

Unique

Unique3 ?
Unique (%)1.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 92
50.8%
<NA> 86
47.5%
183025 1
 
0.6%
206963 1
 
0.6%
600 1
 
0.6%

Length

2023-12-12T12:04:06.044791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:06.193585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 92
50.8%
na 86
47.5%
183025 1
 
0.6%
206963 1
 
0.6%
600 1
 
0.6%

Interactions

2023-12-12T12:03:57.931010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:51.633230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.719582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.400306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.058604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.801377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.721637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.877359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:58.040348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.034883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.811497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.478740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.148357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.894061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.873954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.983444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:58.159042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.143101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.889836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.562517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.240030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.996134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.998325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.117319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:58.294143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.225847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.967219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.635524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.321689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.105589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.135810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.266231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:58.806511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.330768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.053976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.734076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.428176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.213123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.297956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.403103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:58.918039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.419337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.132788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.809378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.508854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.313744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.422770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.534870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:59.031100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.513507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.215914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.888553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.607189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.432103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.577388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.661072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:59.155510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:52.619630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.308327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:53.968113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:54.697742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:55.596779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:56.738667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:57.795099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:04:06.322242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문학단체명사업연도전자책_단권판매_추세3년전(부)전자책_단권판매_추세2년전(부)전자책_단권판매_추세1년전(부)전자책_단권판매_실적(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_실적(부)전자책_총판매부수_추세3년전(부)전자책_총판매부수_추세2년전(부)전자책_총판매부수_추세1년전(부)전자책_총판매부수_실적(부)웹진_연간방문자수_추세3년전(명)웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_실적(명)
문학단체명1.0000.0000.6450.0000.9330.8241.0000.0000.0000.9300.0000.0000.8811.0000.0000.000
사업연도0.0001.0000.0830.0070.0000.0000.0000.0000.0260.0000.0080.0450.0000.0000.0040.045
전자책_단권판매_추세3년전(부)0.6450.0831.0000.9980.9760.9360.5691.0000.7070.9910.9980.9040.8840.5691.0000.835
전자책_단권판매_추세2년전(부)0.0000.0070.9981.0000.9911.0000.0001.0000.7070.9911.0001.0001.0000.0001.0000.835
전자책_단권판매_추세1년전(부)0.9330.0000.9760.9911.0000.8350.0000.5690.5250.9910.9910.9040.8280.0000.7060.623
전자책_단권판매_실적(부)0.8240.0000.9361.0000.8351.0000.0001.0000.6670.8351.0000.9801.0000.0001.0000.980
전자책_정기구독_추세3년전(부)1.0000.0000.5690.0000.0000.0001.0000.0000.0001.0000.0000.0000.0000.6920.0000.000
전자책_정기구독_추세1년전(부)0.0000.0001.0001.0000.5691.0000.0001.0001.0000.5691.0001.0001.0000.0001.0001.000
전자책_정기구독_실적(부)0.0000.0260.7070.7070.5250.6670.0001.0001.0000.5250.7070.6670.9400.0000.9401.000
전자책_총판매부수_추세3년전(부)0.9300.0000.9910.9910.9910.8351.0000.5690.5251.0000.9910.9040.8281.0000.7060.623
전자책_총판매부수_추세2년전(부)0.0000.0080.9981.0000.9911.0000.0001.0000.7070.9911.0001.0001.0000.0001.0000.835
전자책_총판매부수_추세1년전(부)0.0000.0450.9041.0000.9040.9800.0001.0000.6670.9041.0001.0001.0000.0000.6670.884
전자책_총판매부수_실적(부)0.8810.0000.8841.0000.8281.0000.0001.0000.9400.8281.0001.0001.0000.0000.9400.667
웹진_연간방문자수_추세3년전(명)1.0000.0000.5690.0000.0000.0000.6920.0000.0001.0000.0000.0000.0001.0000.0000.000
웹진_연간방문자수_추세1년전(명)0.0000.0041.0001.0000.7061.0000.0001.0000.9400.7061.0000.6670.9400.0001.0001.000
웹진_연간방문자수_실적(명)0.0000.0450.8350.8350.6230.9800.0001.0001.0000.6230.8350.8840.6670.0001.0001.000
2023-12-12T12:04:06.576807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_추세3년전(명)전자책_정기구독_실적(부)전자책_단권판매_추세1년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세2년전(부)웹진_연간방문자수_실적(명)웹진_연간방문자수_추세2년전(명)
웹진_연간방문자수_추세1년전(명)1.0000.0000.6990.6840.9950.0001.0000.9951.000
웹진_연간방문자수_추세3년전(명)0.0001.0000.0000.0000.0000.4861.0000.0001.000
전자책_정기구독_실적(부)0.6990.0001.0000.4580.9950.0001.0000.9951.000
전자책_단권판매_추세1년전(부)0.6840.0000.4581.0000.6770.0001.0000.5481.000
전자책_정기구독_추세1년전(부)0.9950.0000.9950.6771.0000.0001.0000.9891.000
전자책_정기구독_추세3년전(부)0.0000.4860.0000.0000.0001.0001.0000.0001.000
전자책_정기구독_추세2년전(부)1.0001.0001.0001.0001.0001.0001.0001.0001.000
웹진_연간방문자수_실적(명)0.9950.0000.9950.5480.9890.0001.0001.0001.000
웹진_연간방문자수_추세2년전(명)1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T12:04:06.790186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업연도전자책_단권판매_추세3년전(부)전자책_단권판매_추세2년전(부)전자책_단권판매_실적(부)전자책_총판매부수_추세3년전(부)전자책_총판매부수_추세2년전(부)전자책_총판매부수_추세1년전(부)전자책_총판매부수_실적(부)전자책_단권판매_추세1년전(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세2년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_실적(부)웹진_연간방문자수_추세3년전(명)웹진_연간방문자수_추세2년전(명)웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_실적(명)
사업연도1.0000.0050.0520.0900.0040.0570.0550.0930.0000.0001.0000.0000.0410.0001.0000.0000.023
전자책_단권판매_추세3년전(부)0.0051.0000.9020.8241.0000.9010.9010.8210.7790.6771.0000.9840.6840.6761.0000.9890.803
전자책_단권판매_추세2년전(부)0.0520.9021.0000.9160.8970.9990.9990.9130.8600.0001.0000.9840.6840.0001.0000.9890.803
전자책_단권판매_실적(부)0.0900.8240.9161.0000.8200.9160.9161.0000.8030.0001.0000.9890.6920.0001.0000.9950.810
전자책_총판매부수_추세3년전(부)0.0041.0000.8970.8201.0000.8970.8970.8180.8600.9841.0000.6760.4580.9841.0000.6840.548
전자책_총판매부수_추세2년전(부)0.0570.9010.9990.9160.8971.0001.0000.9140.8600.0001.0000.9840.6840.0001.0000.9890.803
전자책_총판매부수_추세1년전(부)0.0550.9010.9990.9160.8971.0001.0000.9140.9030.0001.0000.9890.6920.0001.0000.6920.558
전자책_총판매부수_실적(부)0.0930.8210.9131.0000.8180.9140.9141.0000.8490.0001.0000.9950.6990.0001.0000.6990.692
전자책_단권판매_추세1년전(부)0.0000.7790.8600.8030.8600.8600.9030.8491.0000.0001.0000.6770.4580.0001.0000.6840.548
전자책_정기구독_추세3년전(부)0.0000.6770.0000.0000.9840.0000.0000.0000.0001.0001.0000.0000.0000.4861.0000.0000.000
전자책_정기구독_추세2년전(부)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전자책_정기구독_추세1년전(부)0.0000.9840.9840.9890.6760.9840.9890.9950.6770.0001.0001.0000.9950.0001.0000.9950.989
전자책_정기구독_실적(부)0.0410.6840.6840.6920.4580.6840.6920.6990.4580.0001.0000.9951.0000.0001.0000.6990.995
웹진_연간방문자수_추세3년전(명)0.0000.6760.0000.0000.9840.0000.0000.0000.0000.4861.0000.0000.0001.0001.0000.0000.000
웹진_연간방문자수_추세2년전(명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
웹진_연간방문자수_추세1년전(명)0.0000.9890.9890.9950.6840.9890.6920.6990.6840.0001.0000.9950.6990.0001.0001.0000.995
웹진_연간방문자수_실적(명)0.0230.8030.8030.8100.5480.8030.5580.6920.5480.0001.0000.9890.9950.0001.0000.9951.000

Missing values

2023-12-12T12:03:59.331357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:03:59.591695image/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.
2023-12-12T12:03:59.910106image/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

문학단체명사업연도전자책_단권판매_추세3년전(부)전자책_단권판매_추세2년전(부)전자책_단권판매_추세1년전(부)전자책_단권판매_실적(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세2년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_실적(부)전자책_총판매부수_추세3년전(부)전자책_총판매부수_추세2년전(부)전자책_총판매부수_추세1년전(부)전자책_총판매부수_실적(부)웹진_연간방문자수_추세3년전(명)웹진_연간방문자수_추세2년전(명)웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_실적(명)
0*제**부2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1*국**회2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2*1**학2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3*학**네2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4*학**상2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5*음**사2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6*천**학2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7*행**사2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8*년**작2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9*간**선2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
문학단체명사업연도전자책_단권판매_추세3년전(부)전자책_단권판매_추세2년전(부)전자책_단권판매_추세1년전(부)전자책_단권판매_실적(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세2년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_실적(부)전자책_총판매부수_추세3년전(부)전자책_총판매부수_추세2년전(부)전자책_총판매부수_추세1년전(부)전자책_총판매부수_실적(부)웹진_연간방문자수_추세3년전(명)웹진_연간방문자수_추세2년전(명)웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_실적(명)
171*서**망20190000000000000000
172*와**시20190000000000000000
173*국**회20190000000000000000
174*시**아20190000000000000000
175*국**회20190000000000000000
176*행**사20190000000000000000
177*국**연20190000000000000000
178*대**학20190000000000000000
179*국**회201900050000100000150000600
180*천**학20190000000000000000

Duplicate rows

Most frequently occurring

문학단체명사업연도전자책_단권판매_추세3년전(부)전자책_단권판매_추세2년전(부)전자책_단권판매_추세1년전(부)전자책_단권판매_실적(부)전자책_정기구독_추세3년전(부)전자책_정기구독_추세2년전(부)전자책_정기구독_추세1년전(부)전자책_정기구독_실적(부)전자책_총판매부수_추세3년전(부)전자책_총판매부수_추세2년전(부)전자책_총판매부수_추세1년전(부)전자책_총판매부수_실적(부)웹진_연간방문자수_추세3년전(명)웹진_연간방문자수_추세2년전(명)웹진_연간방문자수_추세1년전(명)웹진_연간방문자수_실적(명)# duplicates
0*국**회2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10
3*국**회2017<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10
4*국**회2018000000000000000010
5*국**회201900000000000000007
2*국**회2016<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5
1*국**회2015<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
6*대**학2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
7*대**학2015<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
8*대**학201900000000000000002