Pandas Query

Another useful function that we’re going to use is pandas' query function.

In the previous lesson, we selected rows in a dataframe by indexing with a mask. Here are those same examples, along with equivalent statements that use query() .

# selecting malignant records in cancer data
df_m = df[df['diagnosis'] == 'M']
df_m = df.query('diagnosis == "M"')

# selecting records of people making over $50K
df_a = df[df['income'] == ' >50K']
df_a = df.query('income == " >50K"')

The examples above filtered columns containing strings. You can also use query to filter columns containing numeric data like this.

# selecting records in cancer data with radius greater than the median
df_h = df[df['radius'] > 13.375]
df_h = df.query('radius > 13.375')

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