Select rows from a Pandas DataFrame based on column values

To select rows from a DataFrame based on column values, we can take the following Steps −

• Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.

• Print the input DataFrame.

• Use df.loc[df["x"]==2] to print the DataFrame when x==2.

• Similarly, print the DataFrame when (x >= 2) and (x < 2).

Example

 Live Demo

import pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 1, 9],       "y": [4, 1, 5, 10],       "z": [4, 1, 5, 0]    } ) print "Given DataFrame is:
", df print "When column x value == 2:
", df.loc[df["x"] == 2] print "When column x value >= 2:
", df.loc[df["x"] >= 2] print "When column x value < 2:
", df.loc[df["x"] < 2]

Output

Given DataFrame is:    x  y  z 0  5  4  4 1  2  1  1 2  1  5  5 3  9 10  0 When column x value == 2:   x  y  z 1 2  1  1 When column x value >= 2:    x  y  z 0  5  4  4 1  2  1  1 3  9 10  0 When column x value < 2:   x  y  z 2 1  5  5