Unexpected behavior when merging multiple CSV files in Pandas - Data misalignment
After trying multiple solutions online, I still can't figure this out. This might be a silly question, but I'm trying to merge multiple CSV files into a single DataFrame using Pandas, but I'm encountering unexpected behavior where the data seems to be misaligned after the merge. I have several CSV files, all with the same structure but with varying numbers of rows. I use `pd.concat()` to merge them, but the resulting DataFrame has rows where the data doesn't match up with the corresponding headers. Here's what I have so far: ```python import pandas as pd # List of CSV files to merge csv_files = ['data1.csv', 'data2.csv', 'data3.csv'] # Merging CSV files merged_data = pd.concat([pd.read_csv(file) for file in csv_files], ignore_index=True) ``` When I check the first few rows of `merged_data`, I see that some columns are not matching with the headers correctly. For example, the first five rows look like this: ``` 0 Value1 Value2 Value3 1 1 A X 2 2 B Y 3 3 C Z 4 4 D W ``` However, the actual data in `data2.csv` looks like this: ``` Value1,Value2,Value3 5,E,X 6,F,Y 7,G,Z ``` I tried checking for extra spaces and ensuring consistent header names across all files, and they all seem correct. I'm using Pandas version `1.3.3` on Python `3.8`. What could be causing this misalignment, and how can I resolve it to get a proper merge? Any insights would be greatly appreciated! Any ideas what could be causing this?