Filter Dataframe pandas with two or more conditions

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I am creating a chart with dataset tips, for this I need to filter the data based on two or more conditions. My goal is to count the number of men, and the number of women. And also count only the number of men smoking and the number of women smoking. The code below does this but adding more conditions gives error. How I can do this filtering using two more conditions?

import pandas as pd
import seaborn as sns

df = sns.load_dataset("tips")

men = df[df.sex=='Male'].count()[0]
women = df[df.sex=='Female'].count()[0]

# isso dar erro
men_smoker = df[df.sex=='Male' & df.smoker=='Yes'].count()[0]

That is the mistake TypeError: unsupported operand type(s) for &: 'str' and 'Categorical'

Dataframe:

    total_bill  tip sex smoker  day time    size
0   16.99   1.01    Female  No  Sun Dinner  2
1   10.34   1.66    Male    No  Sun Dinner  3
2   21.01   3.50    Male    No  Sun Dinner  3
3   23.68   3.31    Male    No  Sun Dinner  2
4   24.59   3.61    Female  No  Sun Dinner  4
python python-3.x pandas

  • It’s python use boolean operator and in place of the bit-to-bit operator &. See the operator table

  • @Augustovasques already tried it doesn’t work either

  • 1

    Each condition has to be between parentheses. Example df[(df[col] == "coisa") & (df[col1] > 10)]. In your case men_smoker = df[(df.sex=='Male') & (df.smoker=='Yes')].count()[0]. When you only have one condition, the parenthesis is not necessary. My suggestion, always use it.

1 answer

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Using & operator, don’t forget to wrap the sub-structures with ().

men_smoker = df[(df.sex=='Male') & (df.smoker=='Yes')].count()[0]

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