categ_analysis.RdRetrieves 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.
categ_analysis(data, input, target)
| 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. |
if input has 1 variable, it retrurns a data frame indicating all the metrics, otherwise prints in console all variable results.
categ_analysis(data_country, "country", "has_flu")#> 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