Imagine I have a dataframe with user events For each user after his last (by timestamp) event I want to add new row with ‘End’ event with the same timestamp as in previous event: I have no idea how to do that. In SQL I would do that with LAG() or LEAD(). But what about pandas? Answer Use DataFrame.drop_duplicates for
Tag: pandas
Merging pandas columns into a new column
Suppose I have a dataframe as follows how can I merge the two columns into one using pandas? The desired output is output Thank you! Answer Use Series.fillna with DataFrame.pop for replace missing values to another column with drop second column: Or you can back filling missing values with select first column by DataFrame.iloc with [[0]] for one column DataFrame
Alternative to apply function in pandas
I would like to execute this simple transformation in a more efficient way. Any ideas? Answer You can use pandas.Series.clip: or numpy.clip:
Add counter as an additional column in Python pandas dataframe
I have following dataframe as an output of my python script. I would like to add another column with count per pmid and add the counter to the first row, keeping the other rows. The dataframe looks like this: df Expected out is: How can I achieve this output? Thanks Answer You can add count for each row with groupby().transform:
Dataframes from dictionnaries in nested lists – Python
I have for example a nested list of 2 lists containing dictionaries like this : [[{},{},{},{}],[{},{},{},{}]] I would like 2 dataframes something like : And I obviously can’t use that : with data as a list of dictionaries. Answer The solution is simply to flatten your list of lists, then you can pass it to pandas normally Will get you
pandas groupby column to list and keep certain values
I have the following dataframe: I create a new column with a list of the all the occupations: How do I only include teacher and student values in occupation_list? Answer You can filter before groupby: Output:
How to modify pandas column if value doesnt match requirements?
I am having trouble to format evenly my pandas df. It is filled with dates and prices for Stocks, but the prices are not formatted equally. From the start of 2021, the values have a comma separating the decimal (cents), but from 1998 to 2020, the prices are not seppareted with comma or dot. How can I add a comma
How can I insert rows to Pandas dataframe depending on previous and next values?
I want to insert a row if the time values between the previous and next rows are high. Essentially I want to have a row for every 2 seconds. So in the below example I want to add 3 rows between 19 and 26. The time values will be 21, 23, 25 and I will later use interpolate method to
Map 2 df but column to value instead of value to value for each ID
I have a table with top 3 reasons (Table 1) and another table with the category it belongs to for each variable (Table 2). I am trying to match the category bins into the reason table like in table 3. Answer Approach index two data frames in way that works with join() then it’s a pd.concat() of each of the
Resample df to smaller time steps and average the counts
I have a dataframe containing counts over time periods (rainfall in periods of 3 hours), something like this: I need to upsample the dataframe into time periods of 1 hour and I would like to average out the counts for the rain, so that there are no NaNs and the total sum of rain remains the same, means this is