Tag: pandas-groupby

i have a df which I want to add a column that shows the student who is place (1) from the group(‘subject’, ‘class’) and update the column after there is a new place (1). code: ╔═════════╦═════════╦═════════╦═══════╗ ║ subject ║ class ║ student ║ place ║ ╠═════════╬═════════╬═════════╬═══════╣ ║ eng ║ Class_4 ║ henry ║ 7 ║ ║ math ║ Class_3 ║

In a dataset like the one below, I’m trying to group the rows by attr_1 and attr_2, and if the sum of the count column exceeds a threshold (in this case 100), I want to keep the original rows. account attr_1 attr_2 count ABC X1 Y1 25 DEF X1 Y1 100 ABC X2 Y2 150 DEF X2 Y2 0 ABC

I have the following dataframe (which is a pretty reduced sample from my original one). I’m trying to get the top 2 ids for each year AND month. So, for example, the idea was to obtain the below df. My main problem here, is to get the Top n along with the dates, because the nlargest method applies to a

I have some data that looks something like this: What I would like to do is to plot the values of the header dates, but grouped by id and period. So essentially this would become 6 line plots, with the x-axis given as the dates. However, maybe I’m just tired, but this data set is weirdly put together imo, so

let’s say I have a data frame like this I wanted to add a new row into each group of groupby(by=[‘eff_date’,’mdl_cd’,’ast_cd’]) in which column value for eff_date,mdl_cd and ast_cd will remain same but for prop_cd value become Hlds and value value column become sum of value of that group e.g. for first group value of value column will be (-0.1234+0.5123+-0.7612)