The Boolean values like True & false and 1&0 can be used as indexes in panda dataframe. They can help us filter out the required records. In the below exampels we will see different methods that can be used to carry out the Boolean indexing operations.
Creating Boolean Index
Let’s consider a data frame desciribing the data from a game. The various points scored on different days are mentioned in a dictionary. Then we can create an index on the dataframe using True and False as the indexing values. Then we can print the final dataframe.
Example
import pandas as pd
# dictionary
game = {'Day':["Monday","Tuesday","Wednesday","Thursday","Friday"], 'points':[31,24,16,11,22]}
df = pd.DataFrame(game,index=[True,False,True,False,True])
print(df)Running the above code gives us the following result
Output
Day points True Monday 31 False Tuesday 24 True Wednesday 16 False Thursday 11 True Friday 22
Using .loc[]
This function can be used to filter out records that has a specific Boolean value. In the below example we can see fetch only the records where the Boolean value is True.
Example
import pandas as pd
# dictionary
game = {'Day':["Monday","Tuesday","Wednesday","Thursday","Friday"], 'points':[31,24,16,11,22]}
df = pd.DataFrame(game,index=[True,False,True,False,True])
#print(df)
print(df.loc[True])Running the above code gives us the following result
Output
Day points True Monday 31 True Wednesday 16 True Friday 22
Using .ix[]
In this method we also use integers as Boolean values. So we change the True and False values in the dataframe to 1 and 0. Then use them to filter out the records.
Example
import pandas as pd
# dictionary
game = {'Day':["Monday","Tuesday","Wednesday","Thursday","Friday"], 'points':[31,24,16,11,22]}
df = pd.DataFrame(game,index=[1,1,0,0,1])
#print(df)
print(df.ix[0])Running the above code gives us the following result:
Output
Day points 0 Wednesday 16 0 T hursday 11