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LangChainframework~30 mins

Loading CSV and Excel files in LangChain - Mini Project: Build & Apply

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Loading CSV and Excel files with Langchain
📖 Scenario: You work in a small company that wants to quickly load data from CSV and Excel files to analyze customer information. You will use Langchain's file loaders to read these files easily.
🎯 Goal: Build a simple Python script using Langchain to load data from a CSV file and an Excel file, preparing the data for further processing.
📋 What You'll Learn
Create a CSV file loader using Langchain
Create an Excel file loader using Langchain
Load data from both files
Print the loaded data content
💡 Why This Matters
🌍 Real World
Loading data from CSV and Excel files is common in business to analyze customer or sales data quickly.
💼 Career
Knowing how to use Langchain loaders helps automate data ingestion for AI applications and data pipelines.
Progress0 / 4 steps
1
Setup CSV file loader
Import CSVLoader from langchain.document_loaders and create a variable called csv_loader that loads the file named customers.csv.
LangChain
Need a hint?

Use CSVLoader and pass the file path as file_path="customers.csv".

2
Setup Excel file loader
Import UnstructuredExcelLoader from langchain.document_loaders and create a variable called excel_loader that loads the file named sales.xlsx.
LangChain
Need a hint?

Use UnstructuredExcelLoader and pass the file path as file_path="sales.xlsx".

3
Load data from both files
Use the load() method on csv_loader and excel_loader to load the data. Store the results in variables called csv_data and excel_data respectively.
LangChain
Need a hint?

Call load() on each loader and assign the results to csv_data and excel_data.

4
Print loaded data content
Print the first item of csv_data and excel_data using print() to see the loaded document content.
LangChain
Need a hint?

Use print() to show the first document from each loaded list.