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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
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
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