create a new dataframe from selecting specific rows from existing dataframe python

Question

i have a table in my pandas dataframe. df

id count price
1    2     100
2    7      25
3    3     720
4    7     221
5    8     212
6    2     200

Answer 1

You nedd add () because & has higher precedence than ==:

df3 = df[(df['count'] == '2') & (df['price'] == '100')]
print (df3)
  id count price
0  1     2   100

If need check multiple values use isin:

df4 = df[(df['count'].isin(['2','7'])) & (df['price'].isin(['100', '221']))]
print (df4)
  id count price
0  1     2   100
3  4     7   221

But if check numeric, use:

df3 = df[(df['count'] == 2) & (df['price'] == 100)]
print (df3)

df4 = df[(df['count'].isin([2,7])) & (df['price'].isin([100, 221]))]
print (df4)