158. Working with CSV Files in pandas

Here are 10 Python snippets demonstrating how to work with CSV files using the pandas library for data reading, writing, and manipulation. Each snippet is separated by a delimiter.

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Snippet 1: Reading a CSV File

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import pandas as pd

# Reading a CSV file into a DataFrame
df = pd.read_csv('data.csv')
print(df.head())  # Display the first 5 rows

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Snippet 2: Writing a DataFrame to a CSV File

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import pandas as pd

# Create a sample DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

# Writing DataFrame to CSV
df.to_csv('output.csv', index=False)
print("Data written to 'output.csv'")

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Snippet 3: Reading a CSV File with Custom Delimiters

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import pandas as pd

# Reading a CSV file with a custom delimiter (semicolon)
df = pd.read_csv('data.csv', delimiter=';')
print(df.head())  # Display the first 5 rows

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Snippet 4: Specifying Column Names While Reading CSV

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import pandas as pd

# Reading a CSV file with custom column names
column_names = ['Name', 'Age', 'City']
df = pd.read_csv('data.csv', names=column_names, header=None)
print(df.head())  # Display the first 5 rows

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Snippet 5: Skipping Rows While Reading CSV

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import pandas as pd

# Reading a CSV file while skipping the first two rows
df = pd.read_csv('data.csv', skiprows=2)
print(df.head())  # Display the first 5 rows

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Snippet 6: Reading a CSV with Specific Columns

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import pandas as pd

# Reading specific columns from a CSV file
df = pd.read_csv('data.csv', usecols=['Name', 'Age'])
print(df.head())  # Display the first 5 rows

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Snippet 7: Handling Missing Data While Reading CSV

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import pandas as pd

# Reading a CSV file and filling missing data with a default value
df = pd.read_csv('data.csv', na_values='NA')
df.fillna(0, inplace=True)  # Replace all NaN with 0
print(df.head())  # Display the first 5 rows

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Snippet 8: Appending Data to an Existing CSV

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import pandas as pd

# Create a new DataFrame
data = {'Name': ['David'], 'Age': [40], 'City': ['New York']}
df_new = pd.DataFrame(data)

# Appending new data to an existing CSV file
df_new.to_csv('data.csv', mode='a', header=False, index=False)
print("New data appended to 'data.csv'")

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Snippet 9: Writing a DataFrame with Custom Index

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import pandas as pd

# Create a sample DataFrame
data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)

# Writing DataFrame to CSV with a custom index
df.to_csv('output.csv', index_label='ID')
print("Data written to 'output.csv' with custom index.")

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Snippet 10: Reading a CSV with Encoding

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import pandas as pd

# Reading a CSV file with a specific encoding (e.g., UTF-8)
df = pd.read_csv('data.csv', encoding='utf-8')
print(df.head())  # Display the first 5 rows

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