Selecting a row of pandas series/dataframe by integer index

The battle of iloc vs loc

What warfare is iloc trained for?

The iloc attribute is skilled in integer-based indexing, following Python's indexing conventions. It's like the list you've always dreamed of!

Why would df[2] lead to a disaster?

Giving df[2] a shot? Think again! Pandas interprets this as looking for a column labeled '2', not accessing the 3rd row.

The charming art of slicing

If you're slicing with the [] operator, such as df[2:3], you've suddenly shifted to integer location selection, but not the exact row index.

Who would win in a showdown, iloc or loc?

While iloc serves integer-based indexing, loc dishes out label-based indexing. This means df.loc[2] seeks a row labeled '2', not the 2nd row.

The fallen warrior, ix

df.ix is the fallen legend of mixed-integer-label-based indexing. It has retired to bed after causing more confusion than convenience.

Direct integer indexing with a sprinkle of pandas magic

Numpy arrays - Fast and Furious

Pandas plays nicely with NumPy. Convert your DataFrame to a NumPy array for direct integer indexing:

# From DataFrame to NumPy - The Transmogrification
np_df = df.to_numpy()
row = np_df[2]
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The enigmatic 'SettingWithCopyWarning'

Beware the SettingWithCopyWarning. It's reality TV for dataframes! Make sure you understand the drama of views vs copies while dealing with pandas.

The Python-Pandas paradox

Pandas is based on dict of Series, making it inherently different from Python indexing conventions. Our beloved library marches to its own drum beat.

Practical play and tips

Conducting a health checkup

Check your DataFrame's structure with df.index before integer indexing to avoid unexpected results. It's like getting your vitals checked before a marathon!

404 Row not found

Accessing a row out of the DataFrame's range with iloc invites an IndexError. Remember to fit within the bounds!

The intriguing multilevel indices

With multilevel indices in your DataFrame, iloc still provides access to rows, but things get messy. To learn this dance, consult the holy documentation.

Performance pep talk

Large dataset? .iloc is your speedster! It excels at rapid row access as it skips the ceremony of label lookups.