Joins and Merge with Pandas in Python | By Govind Sharma
In pandas, you can use joins and merges to combine data from multiple DataFrames based on common columns or indices. Here's an overview of how to use joins and merges in pandas:
Load your data into pandas DataFrames. For example:
import pandas as pd
df1 = pd.read_csv("data1.csv")
df2 = pd.read_csv("data2.csv")
merged_data = pd.merge(df1, df2, on='key')
joined_data = df1.join(df2, how='inner')
You can also use the concat() function to combine DataFrames vertically:
concatenated_data = pd.concat([df1, df2])
Here's the complete code for using joins and merges in pandas:
import pandas as pd
df1 = pd.read_csv("data1.csv")
df2 = pd.read_csv("data2.csv")
merged_data = pd.merge(df1, df2, on='key')
joined_data = df1.join(df2, how='inner')
concatenated_data = pd.concat([df1, df2])
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Tools Covered
Python
Excel
NumPy
Pandas
SciPy
And Many More..