grouping

问题 I have a data frame that has a 3 columns. Time represents every day of the month for various months. what I am trying to do is get the 'Count' value per day and average it per each month, and do this for each country. The output must be in the form of a data frame. Curent data: Time Country Count 2017-01-01 us 7827 2017-01-02 us 7748 2017-01-03 us 7653 .. .. 2017-01-30 us 5432 2017-01-31 us 2942 2017-01-01 us 5829 2017-01-02 ca 9843 2017-01-03 ca 7845 .. .. 2017-01-30 ca 8654 2017-01-31 ca

问题 I have a data frame that has a 3 columns. Time represents every day of the month for various months. what I am trying to do is get the 'Count' value per day and average it per each month, and do this for each country. The output must be in the form of a data frame. Curent data: Time Country Count 2017-01-01 us 7827 2017-01-02 us 7748 2017-01-03 us 7653 .. .. 2017-01-30 us 5432 2017-01-31 us 2942 2017-01-01 us 5829 2017-01-02 ca 9843 2017-01-03 ca 7845 .. .. 2017-01-30 ca 8654 2017-01-31 ca

问题 I have a data frame that has a 3 columns. Time represents every day of the month for various months. what I am trying to do is get the 'Count' value per day and average it per each month, and do this for each country. The output must be in the form of a data frame. Curent data: Time Country Count 2017-01-01 us 7827 2017-01-02 us 7748 2017-01-03 us 7653 .. .. 2017-01-30 us 5432 2017-01-31 us 2942 2017-01-01 us 5829 2017-01-02 ca 9843 2017-01-03 ca 7845 .. .. 2017-01-30 ca 8654 2017-01-31 ca

问题 I'm building a grouped bar chart by nesting a .csv file. The chart will also be viewable as a line chart, so I want a nesting structure that suits the line object. My original .csv looks like this: Month,Actual,Forecast,Budget Jul-14,200000,-,74073.86651 Aug-14,198426.57,-,155530.2499 Sep-14,290681.62,-,220881.4631 Oct-14,362974.9,-,314506.6437 Nov-14,397662.09,-,382407.67 Dec-14,512434.27,-,442192.1932 Jan-15,511470.25,511470.25,495847.6137 Feb-15,-,536472.5467,520849.9105 Mar-15,-,612579

问题 I'm building a grouped bar chart by nesting a .csv file. The chart will also be viewable as a line chart, so I want a nesting structure that suits the line object. My original .csv looks like this: Month,Actual,Forecast,Budget Jul-14,200000,-,74073.86651 Aug-14,198426.57,-,155530.2499 Sep-14,290681.62,-,220881.4631 Oct-14,362974.9,-,314506.6437 Nov-14,397662.09,-,382407.67 Dec-14,512434.27,-,442192.1932 Jan-15,511470.25,511470.25,495847.6137 Feb-15,-,536472.5467,520849.9105 Mar-15,-,612579

问题 I'm building a grouped bar chart by nesting a .csv file. The chart will also be viewable as a line chart, so I want a nesting structure that suits the line object. My original .csv looks like this: Month,Actual,Forecast,Budget Jul-14,200000,-,74073.86651 Aug-14,198426.57,-,155530.2499 Sep-14,290681.62,-,220881.4631 Oct-14,362974.9,-,314506.6437 Nov-14,397662.09,-,382407.67 Dec-14,512434.27,-,442192.1932 Jan-15,511470.25,511470.25,495847.6137 Feb-15,-,536472.5467,520849.9105 Mar-15,-,612579

问题 I'm building a grouped bar chart by nesting a .csv file. The chart will also be viewable as a line chart, so I want a nesting structure that suits the line object. My original .csv looks like this: Month,Actual,Forecast,Budget Jul-14,200000,-,74073.86651 Aug-14,198426.57,-,155530.2499 Sep-14,290681.62,-,220881.4631 Oct-14,362974.9,-,314506.6437 Nov-14,397662.09,-,382407.67 Dec-14,512434.27,-,442192.1932 Jan-15,511470.25,511470.25,495847.6137 Feb-15,-,536472.5467,520849.9105 Mar-15,-,612579

问题 I have a CVS file which has data for different countries at different weeks of this year. I want to create a summary dataframe (within r) grouping together data for weeks 21-24 and weeks 37-41. The data is set as attached example: I am a beginner and not sure where to start. Thanks 回答1: We can use case_when to construct a grouping column based on the substring in the 'year_week' as well as do the grouping on 'country' and summarise the sum of 'new_cases` library(dplyr) library(stringr) df1 %>

问题 I have three related arrays of equal length containing product details. I am trying merge them, group the columnar data (based on id, size, and color), and keep a running count of each unique product. My code: $a1 = array(1,1,1,2,5,1); $a2 = array("m","m","m","s","xl","s"); $a3 = array("color","color","color3","color1","color2","color1",); $temp = []; foreach($a1 as $index => $product_id) { $size = $a2[$index]; $colors = $a3[$index]; // if an entry for given product id and size combination

问题 I have a data.frame with many rows and columns and I want to calculate the mean difference of each value to each of the other values within a group. Here an example: ID value 1 4 1 5 1 7 2 8 2 6 2 5 2 6 This is what I want to calculate: ID value value_mean_diff 1 4 (4-5)^2 + (4-7)^2 /groupsize = 3 1 5 (5-4)^2 + (5-7)^2 / 3 1 7 (7-4)^2 + (7-5)^2 / 3 2 8 (8-6)^2 + (8-5)^2 + (8-6)^2 / 4 2 6 (6-8)^2 + (6-5)^2 + (6-6)^2 / 4 2 5 (5-8)^2 + (5-6)^2 + (5-6)^2 / 4 2 6 (6-8)^2 + (6-6)^2 + (6-5)^2 / 4 I