Dataframe filtering rows by column values

Question

I have a Dataframe df

       Num1   Num2 
one       1      0
two       3      2
three     5      4
four      7      6
five      9      8

I want to filter rows that have value bigger than 3 in Num1 and smaller than 8 in Num2.

I tried this

df = df[df['Num1'] > 3 and df['Num2'] < 8]

but the error occurred.

ValueError: The truth value of a Series is ambiguous.

so I used

df = df[df['Num1'] > 3]
df = df[df['Num2'] < 8]

I think the code can be shorter.

Is there any other way?

Answer 1

You need add () because operator precedence with bit-wise operator &:

df1 = df[(df['Num1'] > 3) & (df['Num2'] < 8)]
print (df1)
       Num1  Num2
three     5     4
four      7     6

Better explanation is here.

Or if need shortest code use query:

df1 = df.query("Num1 > 3 and Num2 < 8")
print (df1)
       Num1  Num2
three     5     4
four      7     6

---

df1 = df.query("Num1 > 3 &  Num2 < 8")
print (df1)
       Num1  Num2
three     5     4
four      7     6

Answer 2

Yes, you can use the & operator:

df = df[(df['Num1'] > 3) & (df['Num2'] < 8)]
#                        ^ & operator

This is because and works on the truthiness value of the two operands, whereas the & operator can be defined on arbitrary data structures.

The brackets are mandatory here, because & binds shorter than > and <, so without brackets, Python would read the expression as df['Num1'] > (3 & df['Num2']) < 8.

Note that you can use the | operator as a logical or.