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Essential Pandas Functions for Data Analysis
Data Loading:
pd.read_csv() - Load data from a CSV file.
pd.read_excel() - Load data from an Excel file.
Data Inspection:
df.head(n) - View the first n rows.
df.info() - Get a summary of the dataset.
df.describe() - Generate summary statistics.
Data Manipulation:
df.drop(columns=['col1', 'col2']) - Remove specific columns.
df.rename(columns={'old_name': 'new_name'}) - Rename columns.
df['col'] = df['col'].apply(func) - Apply a function to a column.
Filtering and Sorting:
df[df['col'] > value] - Filter rows based on a condition.
df.sort_values(by='col', ascending=True) - Sort rows by a column.
Aggregation:
df.groupby('col').sum() - Group data and compute the sum.
df['col'].value_counts() - Count unique values in a column.
Merging and Joining:
pd.merge(df1, df2, on='key') - Merge two DataFrames.
pd.concat([df1, df2]) - Concatenate
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