write code to join dataset folder in google collab in python

To join two datasets in Google Colab using Python, you can use Pandas. Here's an example of the code that shows how to merge two datasets based on a common column.

Firstly, you need to import the necessary libraries and mount your Google Drive:

main.py
import pandas as pd
from google.colab import drive

drive.mount('/content/drive')
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Then, you can load the two datasets into two Pandas data frames:

main.py
df1 = pd.read_csv('/content/drive/MyDrive/dataset1.csv')
df2 = pd.read_csv('/content/drive/MyDrive/dataset2.csv')
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After loading the datasets, you can merge them using the merge function from Pandas:

main.py
merged_df = pd.merge(df1, df2, on='common_column')
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In the merge function, on specifies the column that is common between the two datasets.

Finally, you can save the merged dataset to a new csv file using the to_csv function:

main.py
merged_df.to_csv('/content/drive/MyDrive/merged_dataset.csv', index=False)
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In this example, the merged dataset is saved as merged_dataset.csv in the root folder of your Google Drive.

Note that /content/drive/MyDrive/ is the path to your Google Drive folder where your datasets are stored. Please adjust the path according to the location of your datasets.