We need to create a Dataframe with multiple columns and rows where we will check if a column has zero values only.
import pandas as pd
employees = [
['Robin', 30, 0, 'India'],
['Rick', 35, 0, 'US'],
['Tony Stark', 24, 0, 'US'],
['Roney', 24, 0, 'Canada'],
['Sumit', 24, 0, 'India'],
['Parek Bisth', 24, 0, 'India']
]
# create dataframe
df = pd.DataFrame(employees, columns=['Name', 'Age', 'PeerCount', 'Country'])
print(df)
Output
Name Age PeerCount Country
0 Robin 30 0 India
1 Rick 35 0 US
2 Tony Stark 24 0 US
3 Roney 24 0 Canada
4 Sumit 24 0 India
5 Parek Bisth 24 0 India
We will use the all() function to check whether a column contains zero value rows only. We will be using the below code to check that.
Check if the 'Age' column contains zero values only
# check if Age column contains 0 values only
if (df['Age'] == 0).all():
print('All values in Age column are zero')
else:
print('All values in Age column are not zero')
Output
All values in Age column are not zero
Check if the 'PeerCount' column contains zero values only
# check if PeerCount column contains 0 values only
if (df['PeerCount'] == 0).all():
print('All values in PeerCount column are zero')
else:
print('All values in PeerCount column are not zero')
Output
All values in PeerCount column are zero
Full Code Example
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