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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:\n", df
print "When column x value == 2:\n", df.loc[df["x"] == 2]
print "When column x value >= 2:\n", df.loc[df["x"] >= 2]
print "When column x value < 2:\n", 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
Updated on 30-Aug-2021 09:13:15
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