0
I have a question to configure the filters "e" and "ou" in the pandas.
Example: A column with the following col1 values (yes, no, maybe)
to get the yes OK
df[df['col1']=='sim']
Now, to catch:
yes or no
yes and no
yes and yes
How would you do?
1
You can use the operator | to define the OR operation, or the operator & for operation E.
df[df['col1'] == 'sim' | df['col1'] == 'nao'] # Retorna se for "sim" ou "nao"
df[df['col1'] == 'sim' & df['col1'] == 'nao'] # Retorna se for "sim" e "nao" (nunca)
In OR, you can simplify using the method isin:
df[df['col1'].isin(['sim', 'nao'])] # Retorna se for "sim" ou "nao"
0
A more intuitive way to do this is by using the query command, but in terms of performance is not as fast as a pandas' isin:
Yes or No
df.query("col1 == 'sim' or col1 == 'nao'")
Yes and No / this never happens
df.query("col1 == 'sim' and col1 == 'nao'")
Yes or Yes / ambiguous
df.query("col1 == 'sim' and col1 == 'sim'")
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