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`DataFrame` Indexing and Loading

Introduction to CSV Files​

  • CSV (Comma Separated Values): A lightweight, ubiquitous format for data storage.
    • Commonly used by spreadsheet software like Excel and Google Sheets.
    • Format is flexible but lacks a strict specification, leading to possible variations in structure.

Viewing CSV File Contents​

  • Viewing CSV Files with Shell Commands:
    • Jupyter notebooks can integrate shell commands using an exclamation mark (!).
    • Example: Using !cat to display the contents of a CSV file: 
      !cat datasets/Admission_Predict.csv

Loading CSV Data into a DataFrame​

  • Import pandas:

    import pandas as pd

  • Loading Data:

    df = pd.read_csv('datasets/Admission_Predict.csv')

  • Viewing Data:

    df.head()

Setting a Specific Column as the Index​

  • Using index_col parameter: 
    df = pd.read_csv('datasets/Admission_Predict.csv', index_col=0)
    df.head()

Renaming Columns​

  • Basic Renaming Using a Dictionary:

    new_df = df.rename(columns={
        'GRE Score': 'GRE Score', 
        'TOEFL Score': 'TOEFL Score',
        'University Rating': 'University Rating', 
        'SOP': 'Statement of Purpose',
        'LOR': 'Letter of Recommendation',
        'CGPA': 'CGPA', 
        'Research': 'Research',
        'Chance of Admit': 'Chance of Admit'
    })
    new_df.head()

  • Identifying Issues with Column Names:

    new_df.columns

  • Addressing Issues with Spaces:

    new_df = new_df.rename(columns={'LOR ': 'Letter of Recommendation'})
    new_df.head()

  • Using str.strip() for Robustness:

    new_df = new_df.rename(mapper=str.strip, axis='columns')
    new_df.head()

Modifying Column Names Directly​

  • Using df.columns Attribute: 
    cols = list(df.columns)
    cols = [x.lower().strip() for x in cols]
    df.columns = cols
    df.head()

Summary​

  • Loading CSV into pandas DataFrame: Utilized pd.read_csv().
  • Basic Data Cleaning: Performed column renaming and handled issues with extra spaces.
  • Direct Column Modification: Demonstrated using lists and list comprehensions for efficient renaming.