categ_analysis: Profiling analysis of categorical vs. target variable
In funModeling: Exploratory Data Analysis and Data Preparation Tool-Box
Description
Usage
Arguments
Value
Examples
View source: R/target_profiling.R
Description
Retrieves a complete summary of the grouped input variable against the target variable. Type of target variable must be binary for now. A positive case will be the less representative one. It returns the total positive cases (sum_target)); pecentage of total positive cases (perc_target) that fell in that category (this column sums 1); likelihood or mean of positive cases (mean_target) measured by the total positive cases over total cases in that category; quantity of rows of that category (q_rows) and in percentage (perc_rows) -this column sums 1.
Usage
1
categ_analysis(data, input, target)
Arguments
data
input data containing the variable to describe
input
string input variable (if empty, it runs for all categorical variable), it can take a single character value or a character vector.
target
string target variable. Binary or two class is only supported by now.
Value
if input has 1 variable, it retrurns a data frame indicating all the metrics, otherwise prints in console all variable results.
Examples
1
categ_analysis(data_country, "country", "has_flu")
Example output
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2
Attaching package: 'Hmisc'
The following objects are masked from 'package:base':
format.pval, round.POSIXt, trunc.POSIXt, units
sh: 1: cannot create /dev/null: Permission denied
funModeling v.1.6.5 :)
Examples and tutorials at livebook.datascienceheroes.com
country mean_target sum_target perc_target q_rows
1 Malaysia 1.000 1 0.012 1
2 Mexico 0.667 2 0.024 3
3 Portugal 0.200 1 0.012 5
4 United Kingdom 0.178 8 0.096 45
5 Uruguay 0.175 11 0.133 63
6 Israel 0.167 1 0.012 6
7 Switzerland 0.167 1 0.012 6
8 Canada 0.158 3 0.036 19
9 France 0.142 41 0.494 288
10 Argentina 0.111 1 0.012 9
11 Germany 0.100 3 0.036 30
12 Australia 0.098 4 0.048 41
13 Romania 0.091 1 0.012 11
14 Spain 0.091 1 0.012 11
15 Sweden 0.083 1 0.012 12
16 Netherlands 0.053 1 0.012 19
17 Turkey 0.030 2 0.024 67
18 Asia/Pacific Region 0.000 0 0.000 1
19 Austria 0.000 0 0.000 1
20 Bangladesh 0.000 0 0.000 3
21 Belgium 0.000 0 0.000 15
22 Bosnia and Herzegovina 0.000 0 0.000 1
23 Brazil 0.000 0 0.000 13
24 Bulgaria 0.000 0 0.000 9
25 Cambodia 0.000 0 0.000 3
26 Chile 0.000 0 0.000 2
27 China 0.000 0 0.000 65
28 Costa Rica 0.000 0 0.000 2
29 Croatia 0.000 0 0.000 2
30 Cyprus 0.000 0 0.000 1
31 Czech Republic 0.000 0 0.000 1
32 Denmark 0.000 0 0.000 6
33 Dominican Republic 0.000 0 0.000 1
34 Egypt 0.000 0 0.000 2
35 Finland 0.000 0 0.000 4
36 Ghana 0.000 0 0.000 1
37 Greece 0.000 0 0.000 1
38 Honduras 0.000 0 0.000 4
39 Hong Kong 0.000 0 0.000 9
40 Indonesia 0.000 0 0.000 6
41 Iran, Islamic Republic of 0.000 0 0.000 1
42 Ireland 0.000 0 0.000 1
43 Isle of Man 0.000 0 0.000 1
44 Italy 0.000 0 0.000 10
45 Japan 0.000 0 0.000 18
46 Korea, Republic of 0.000 0 0.000 4
47 Latvia 0.000 0 0.000 1
48 Lithuania 0.000 0 0.000 1
49 Luxembourg 0.000 0 0.000 1
50 Malta 0.000 0 0.000 2
51 Moldova, Republic of 0.000 0 0.000 1
52 Montenegro 0.000 0 0.000 1
53 Morocco 0.000 0 0.000 5
54 New Zealand 0.000 0 0.000 4
55 Norway 0.000 0 0.000 6
56 Pakistan 0.000 0 0.000 3
57 Palestinian Territory 0.000 0 0.000 1
58 Peru 0.000 0 0.000 2
59 Philippines 0.000 0 0.000 7
60 Poland 0.000 0 0.000 13
61 Russian Federation 0.000 0 0.000 5
62 Saudi Arabia 0.000 0 0.000 3
63 Senegal 0.000 0 0.000 1
64 Singapore 0.000 0 0.000 8
65 Slovenia 0.000 0 0.000 1
66 South Africa 0.000 0 0.000 8
67 Taiwan 0.000 0 0.000 3
68 Thailand 0.000 0 0.000 2
69 Ukraine 0.000 0 0.000 6
70 Vietnam 0.000 0 0.000 1
perc_rows
1 0.001
2 0.003
3 0.005
4 0.049
5 0.069
6 0.007
7 0.007
8 0.021
9 0.316
10 0.010
11 0.033
12 0.045
13 0.012
14 0.012
15 0.013
16 0.021
17 0.074
18 0.001
19 0.001
20 0.003
21 0.016
22 0.001
23 0.014
24 0.010
25 0.003
26 0.002
27 0.071
28 0.002
29 0.002
30 0.001
31 0.001
32 0.007
33 0.001
34 0.002
35 0.004
36 0.001
37 0.001
38 0.004
39 0.010
40 0.007
41 0.001
42 0.001
43 0.001
44 0.011
45 0.020
46 0.004
47 0.001
48 0.001
49 0.001
50 0.002
51 0.001
52 0.001
53 0.005
54 0.004
55 0.007
56 0.003
57 0.001
58 0.002
59 0.008
60 0.014
61 0.005
62 0.003
63 0.001
64 0.009
65 0.001
66 0.009
67 0.003
68 0.002
69 0.007
70 0.001
funModeling documentation built on July 1, 2020, 5:40 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Examples
View source: R/target_profiling.R
Description
Retrieves a complete summary of the grouped input variable against the target variable. Type of target variable must be binary for now. A positive case will be the less representative one. It returns the total positive cases (sum_target)); pecentage of total positive cases (perc_target) that fell in that category (this column sums 1); likelihood or mean of positive cases (mean_target) measured by the total positive cases over total cases in that category; quantity of rows of that category (q_rows) and in percentage (perc_rows) -this column sums 1.
Usage
1 | categ_analysis(data, input, target)
|
Arguments
data |
input data containing the variable to describe |
input |
string input variable (if empty, it runs for all categorical variable), it can take a single character value or a character vector. |
target |
string target variable. Binary or two class is only supported by now. |
Value
if input has 1 variable, it retrurns a data frame indicating all the metrics, otherwise prints in console all variable results.
Examples
1 | categ_analysis(data_country, "country", "has_flu")
|
Example output
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2
Attaching package: 'Hmisc'
The following objects are masked from 'package:base':
format.pval, round.POSIXt, trunc.POSIXt, units
sh: 1: cannot create /dev/null: Permission denied
funModeling v.1.6.5 :)
Examples and tutorials at livebook.datascienceheroes.com
country mean_target sum_target perc_target q_rows
1 Malaysia 1.000 1 0.012 1
2 Mexico 0.667 2 0.024 3
3 Portugal 0.200 1 0.012 5
4 United Kingdom 0.178 8 0.096 45
5 Uruguay 0.175 11 0.133 63
6 Israel 0.167 1 0.012 6
7 Switzerland 0.167 1 0.012 6
8 Canada 0.158 3 0.036 19
9 France 0.142 41 0.494 288
10 Argentina 0.111 1 0.012 9
11 Germany 0.100 3 0.036 30
12 Australia 0.098 4 0.048 41
13 Romania 0.091 1 0.012 11
14 Spain 0.091 1 0.012 11
15 Sweden 0.083 1 0.012 12
16 Netherlands 0.053 1 0.012 19
17 Turkey 0.030 2 0.024 67
18 Asia/Pacific Region 0.000 0 0.000 1
19 Austria 0.000 0 0.000 1
20 Bangladesh 0.000 0 0.000 3
21 Belgium 0.000 0 0.000 15
22 Bosnia and Herzegovina 0.000 0 0.000 1
23 Brazil 0.000 0 0.000 13
24 Bulgaria 0.000 0 0.000 9
25 Cambodia 0.000 0 0.000 3
26 Chile 0.000 0 0.000 2
27 China 0.000 0 0.000 65
28 Costa Rica 0.000 0 0.000 2
29 Croatia 0.000 0 0.000 2
30 Cyprus 0.000 0 0.000 1
31 Czech Republic 0.000 0 0.000 1
32 Denmark 0.000 0 0.000 6
33 Dominican Republic 0.000 0 0.000 1
34 Egypt 0.000 0 0.000 2
35 Finland 0.000 0 0.000 4
36 Ghana 0.000 0 0.000 1
37 Greece 0.000 0 0.000 1
38 Honduras 0.000 0 0.000 4
39 Hong Kong 0.000 0 0.000 9
40 Indonesia 0.000 0 0.000 6
41 Iran, Islamic Republic of 0.000 0 0.000 1
42 Ireland 0.000 0 0.000 1
43 Isle of Man 0.000 0 0.000 1
44 Italy 0.000 0 0.000 10
45 Japan 0.000 0 0.000 18
46 Korea, Republic of 0.000 0 0.000 4
47 Latvia 0.000 0 0.000 1
48 Lithuania 0.000 0 0.000 1
49 Luxembourg 0.000 0 0.000 1
50 Malta 0.000 0 0.000 2
51 Moldova, Republic of 0.000 0 0.000 1
52 Montenegro 0.000 0 0.000 1
53 Morocco 0.000 0 0.000 5
54 New Zealand 0.000 0 0.000 4
55 Norway 0.000 0 0.000 6
56 Pakistan 0.000 0 0.000 3
57 Palestinian Territory 0.000 0 0.000 1
58 Peru 0.000 0 0.000 2
59 Philippines 0.000 0 0.000 7
60 Poland 0.000 0 0.000 13
61 Russian Federation 0.000 0 0.000 5
62 Saudi Arabia 0.000 0 0.000 3
63 Senegal 0.000 0 0.000 1
64 Singapore 0.000 0 0.000 8
65 Slovenia 0.000 0 0.000 1
66 South Africa 0.000 0 0.000 8
67 Taiwan 0.000 0 0.000 3
68 Thailand 0.000 0 0.000 2
69 Ukraine 0.000 0 0.000 6
70 Vietnam 0.000 0 0.000 1
perc_rows
1 0.001
2 0.003
3 0.005
4 0.049
5 0.069
6 0.007
7 0.007
8 0.021
9 0.316
10 0.010
11 0.033
12 0.045
13 0.012
14 0.012
15 0.013
16 0.021
17 0.074
18 0.001
19 0.001
20 0.003
21 0.016
22 0.001
23 0.014
24 0.010
25 0.003
26 0.002
27 0.071
28 0.002
29 0.002
30 0.001
31 0.001
32 0.007
33 0.001
34 0.002
35 0.004
36 0.001
37 0.001
38 0.004
39 0.010
40 0.007
41 0.001
42 0.001
43 0.001
44 0.011
45 0.020
46 0.004
47 0.001
48 0.001
49 0.001
50 0.002
51 0.001
52 0.001
53 0.005
54 0.004
55 0.007
56 0.003
57 0.001
58 0.002
59 0.008
60 0.014
61 0.005
62 0.003
63 0.001
64 0.009
65 0.001
66 0.009
67 0.003
68 0.002
69 0.007
70 0.001
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.