I am working on a problem where I have to take user input which is an integer indicating the number of months I have to look back at. For example if I want to look at the data 3 months back I must take input from user as 3. Based on this integer user input I have to filter my
Tag: pandas
Creating a Dummy Variable Using Groupby and Max Functions With Pandas
I am trying to create a dummy variable that takes on the value of “1” if it has the largest democracy value in a given year using pandas. I have tried numerous iterations of code, but none of them accomplish what I am trying to do. I will provide some code and discuss the errors that I am dealing …
For each date – is it between any of the provided date bounds?
Data: df: df_cal: Expected result: Goal: I want to assign values to a new column col: to 1 if df.index is between any of df_cal date ranges, and to 0 otherwise. Reference: I refer this post. But it just works for one condition and mine is lots of date ranges. And I don’t want to use dataframe join metho…
GroupBy results to list of dictionaries, Using the grouped by object in it
My DataFrame looks like so: And I’m looking to group it by Date and extract that data to a list of dictionaries so it appears like this: This is my code so far: Using this method can’t use my grouped by objects in the apply method itself: Using to_dict() giving me the option to reach the grouped b…
Can apply function change the original input pandas df?
I always assume that the apply function won’t change the original pandas dataframe and need the assignment to return the changes, however, could anyone help to explain why this happen? returns So, apply function changed the original pd.DataFrame without return, but if there’s an non-basic type col…
Apply strip() to all cells in dataframe with multiple data types
I have a dataframe that has multiple data types. Part of my processing code is to apply the strip() function before I work on the df. My example df: Here is my code: It doesn’t seem to be processing for all strings though. I’m still seeing spaces before and after in some of my output cells. Questi…
How to drop duplicates in pandas but keep more than the first
Let’s say I have a pandas DataFrame: I want to drop duplicates if they exceed a certain threshold n and replace them with that minimum. Let’s say that n=3. Then, my target dataframe is EDIT: Each set of consecutive repetitions is considered separately. In this example, rows 8 and 9 should be kept.…
Pandas Styler conditional formatting based on comparison of each row with last row
I have a large dataframe that comes from calculation with varying number of columns and rows: Each column has last row that decides coloring of each cell in that column. Each cell of the column needs to be compared with the last cell of that particular column and then the condition to be applied is: if s>s…
Taking the 1st and 2nd, 4th and 5th etc rows from a single Pandas column and put in two new columns, Python
Below is a sample of a pandas dataframe, a single column with 1000’s of rows. I need second/third columns putting data in rows 1 and 2, 4 and 5 etc in the second/third column Desired Output Can only manage to pull out the odds with: Suggestions? Answer Make three subsets by taking every third value R…
how to save space training
I have written an intent classification program. This is first trained with training data and then tested with test data. The training process takes a few seconds. What is the best way to save such a training, so that it does not have to be trained again with every call? Is it enough to save train_X and train…