I’m working with data from an excel file like this. I’m using this line of code to eliminate the duplicates keeping the maximum df_clean=df_raw.sort_values(‘A’, ascending=False).drop_duplicates(‘B’).sort_index() but I’m obtaining this error Index([‘B’], dtype=’object’) I don’t know which could be the problem since I’m doing it after the upload of the file. Answer If I can assume that your index is just
Tag: pandas
Trying to get ‘QS’ frequency in pandas for a datetime64[ns] gives attribute error
I am working with an external data source and I am trying to get Quaterstart(QS) frequency for a particular data field. I am providing a dummy data and code below. I am gettinng the following error when I run this Can someone please help me understand what’s happening here? ps: The data given here is dummy data and not the
Slice pandas row of a specific column using numpy boolean
The objective is to slice multiple pandas row of a specific column using a Numpy boolean. The following code should do the task However, I wonder whether the above code can be shortened further, especially these lines Currently, Pandas throw an error if I am to directly using Numpy boolean without converting to list Is there something I miss, or
Convert Hour Minute Second Milisecond to total second.milisecond in latest pandas version
I have csv file with format HH:MM:SS.Milisecond I want convert that to How to do that in Pandas latest version (1.4)? I’ve tried some answers from this forum, but they don’t work on csv and latest version of Pandas. Answer Assuming this input: You can use pandas.Timedelta.total_seconds: output:
Plot Between Certain Y axis Values
I’m plotting some values using Pandas. But my Values are soo close together It doesn’t actually show anything. Is there a way to restrict Y-axis to “Zoom in” on the differences? And then really show the difference between the value even though there isn’t much..? Answer You can adjust the y-axis start and end by replacing the last line bplot.plot.bar(
How do I overlay multiple sns distplots or change the colour based on a secondary variable using a pandas df
I have a pandas dataframe with a ‘frequency_mhz’ variable and a ‘type’ variable. I want to create a dist plot using seaborne that overlays all of the frequencys but changes the colour based on the ‘type’. Is there a way I can overlay the 3 into one plot? or a way ive missed to change the colour of the bars
Pandas – Compare each row with one another across dataframe and list the amount of duplicate values
I would like to add a column to an existing dataframe that compares every row in the dataframe against each other and list the amount of duplicate values. (I don’t want to remove any of the rows, even if they are entirely duplicated with another row) The duplicates column should show something like this: Answer IIUC, you can convert your
Remove rows in a group by until the last row meets some condition
I have the following df We can assume that this data is already sorted. What i need to do is, for every id, I need to remove rows under the following conditions the first entry for every id is type A the last entry for every id is type B the last entry’s B is the last one that appears
Get a value from dataframe with different shape based on two columns
I have two dataframes colored by approximately matching marks: df1: df2: The “marks” are not the same in each of them, but some are close. How can I copy the “Evaluated” value from df2 to df1 based on relevant “name” and “mark”? My code is: Expected result is df3 df3: How can I do an approximate match and get the
Checking Previous elements in a list with Python and based on the previous element store a value in a new column with Pandas
I have a table which contains 2 columns. the code will check the previous element of list and look for ( Startup / Shutdown ) : Example : if a Crash is after a Startup ; State column will be filled with Startup in front of that Crash as the table below : Crashes State Crash in A Startup Crash