👀 Views: 0 💬 Answers: 1 📅 Created: 2025-06-19

pandas dataframe pivot Python

I'm collaborating on a project where I'm dealing with I'm working through a tutorial and This might be a silly question, but I've tried everything I can think of but I need help solving After trying multiple solutions online, I still can't figure this out. I'm having trouble with pivoting a DataFrame that has MultiIndex columns. When I try to pivot my DataFrame, the resulting DataFrame has unexpected data types, leading to issues with subsequent calculations. Specifically, I have a DataFrame where the columns are structured as a MultiIndex with 'Category' and 'Subcategory'. Here’s a simplified version of my DataFrame: ```python import pandas as pd data = { ('A', 'a1'): [1, 2], ('A', 'a2'): [3, 4], ('B', 'b1'): [5, 6], ('B', 'b2'): [7, 8] } index = ['row1', 'row2'] df = pd.DataFrame(data, index=index) df.columns = pd.MultiIndex.from_tuples(df.columns) ``` When I attempt to pivot the DataFrame to get the sums for each category like this: ```python pivot_df = df.stack().reset_index().pivot_table(index='level_0', columns='level_1', values=0, aggfunc='sum') ``` I expect to get a DataFrame where the values are all integers, but instead, I get mixed types, including floats. The floating-point numbers are causing issues later in my calculations where I need integers for certain operations. Additionally, when I inspect the pivoted DataFrame with `pivot_df.dtypes`, I see: ``` A float64 B float64 dtype: object ``` I’ve tried using the `astype(int)` method to convert the columns back to integers, but it raises a `ValueError` due to NaN values in the DataFrame. I initially thought that pivoting would maintain the data types, but it seems to be converting everything to float. How can I ensure that my pivoted DataFrame retains integer types and handles NaN values appropriately? Is there a better approach to achieving my goal without losing the original data types? I'm using Pandas version 1.5.0. Any advice or best practices would be greatly appreciated! This is part of a larger CLI tool I'm building. Is this even possible? I'm developing on Ubuntu 22.04 with Python. Is there a better approach? What am I doing wrong? I'm coming from a different tech stack and learning Python. Any advice would be much appreciated. I'm coming from a different tech stack and learning Python. My development environment is Debian. What are your experiences with this?