Basics commmands for the Pandas Python lib.

Pandas Cheat Sheet

Importing and Creating Data Structures

• Importing Pandas: import pandas as pd
• Series: s = pd.Series([1, 3, 5, np.nan, 6, 8])
• DataFrame:
  • df = pd.DataFrame(np.random.randn(6, 4), columns=list('ABCD'))
  • df = pd.DataFrame([{'A': 0, 'B': 1}, {'A': 2, 'B': 3}])

Viewing Data

• Display the top rows: df.head(n)
• Display the bottom rows: df.tail(n)
• Display basic statistics: df.describe()
• Display column data types: df.dtypes

Selection

• Select a column: df['column_name']
• Select multiple columns: df[['column_name1', 'column_name2']]
• Select rows by index: df.iloc[3], df.iloc[2:5]
• Select rows by condition: df[df['column_name'] > 2]

Data Cleaning

• Drop rows with missing values: df.dropna(axis=0)
• Fill missing values: df.fillna(value)
• Replace values: df.replace(to_replace, value)

Data Operations

• Apply a function: df.apply(np.mean)
• Sort by values: df.sort_values(by='column_name')
• Group by values: df.groupby('column_name').sum()

Merging Data

• Inner Join: pd.merge(df1, df2, on='key')
• Left Join: pd.merge(df1, df2, on='key', how='left')
• Right Join: pd.merge(df1, df2, on='key', how='right')
• Full Outer Join: pd.merge(df1, df2, on='key', how='outer')
• Concatenate DataFrames: pd.concat([df1, df2])

Input and Output

• Read from CSV: df = pd.read_csv('file.csv')
• Write to CSV: df.to_csv('file.csv', index=False)
• Read from Excel: df = pd.read_excel('file.xlsx')
• Write to Excel: df.to_excel('file.xlsx', sheet_name='Sheet1', index=False)

Handling Dates

• Convert to datetime: df['date_column'] = pd.to_datetime(df['date_column'])
• Set as index: df.set_index('date_column', inplace=True)
• Resample time series data: df.resample('M').mean()

Plotting

• Basic plot: df.plot()
• Histogram: df['column_name'].plot.hist(bins=20)
• Bar plot: df.plot.bar()
• Scatter plot: df.plot.scatter(x='column_name1', y='column_name2')