Question

How do I index/slice tabular data in Python?

Answer 1

To index or slice tabular data in Python, the pandas library's DataFrame object is used. Integer-based indexing can be performed with .iloc[], while label-based indexing is done with .loc[]. These methods allow selective data retrieval by specifying rows and columns.

Step-by-step explanation:

To index/slice tabular data in Python, one commonly uses libraries such as pandas. Pandas provide a DataFrame object that can be used for storing and manipulating tabular data with rows and columns. To slice data from a DataFrame, you can use indexing just like you would with lists, or better yet, use the .loc and .iloc methods provided by pandas.

Here is a simple example:

• .iloc[] is used for selecting by integer location, which means you use integer indices to select specific rows or columns (e.g., df.iloc[0] will give you the first row).
• .loc[] is used for selecting by label, which lets you use the names of the rows or columns to select data (e.g., df.loc['row1'] will give you the row labeled 'row1').

If you want to select a range of rows and a specific column, you could use:

• df.iloc[0:5, column_index] - Selects rows 0 to 4 of the column with the specified index.
• df.loc[row_start:row_end, 'column_name'] - Selects a range of rows with an explicit column name.