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Data pipelines & processing

ETL-style flows, batch transforms, validation, and moving data between formats.

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Data pipelines & processing easy

Union Multiple DataFrames with Aligned Columns in Python

Concatenate DataFrames with different columns, aligning them and filling missing values with NaN using pandas concat.

pandas dataframes concat
Python 
import pandas as pd
from io import StringIO

# Sample dataframes with different columns
df1 = pd.DataFrame({
    'id': [1, 2, 3],
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 30, 35]
})

df2 = pd.DataFrame({
    'id': [4, 5],
    'name': ['Diana', 'Eve'],
    'city': ['NYC', 'LA']
})

df3 = pd.DataFrame({
…
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