Converting cells in a dataframe to binary values depending on the presence of a certain string-CodePudding

I have a dataframe with a column called player_traits, which contains traits for each player, e.g. 'Injury Prone', 'Long Shot Taker', 'Power Header' etc.

I want to change this column so that if 'Injury Prone' is present the cell's value is converted to 1, and if 'Injury Prone' is not present the cell's value is converted 0

Any tips much appreciated

CodePudding user response：

import pandas as pd
x = pd.DataFrame({"player_traits": ['Injury Prone', 'Long Shot Taker', 'Power Header']})

The data:

      player_traits
 0     Injury Prone
 1  Long Shot Taker
 2     Power Header

We can use the following code:

x["player_traits"] = (x["player_traits"] == "Injury Prone").astype(int)

Which gives:

     player_traits
0                1
1                0
2                0

CodePudding user response：

This will cycle through all of your different traits and assign a binary value for them:

###### Recreate OP's data########
import pandas as pd
traits = ['Injury Prone', 'Long Shot Taker', 'Power Header']
players = ["Player1", "Player2"]
player_traits = ['Injury Prone, Long Shot Taker', 'Power Header']
df = pd.DataFrame({"Player":players, "Player_Traits":player_traits})
#################################

pTraits = []
for x in df.Player_Traits:
    binary = "".join(["1" if y in x else "0" for y in traits])
    pTraits.append(binary)
df["Binary"] = pTraits
df

Ouput:


    Player  Player_Traits                   Binary
0   Player1 Injury Prone, Long Shot Taker   110
1   Player2 Power Header                    001

You can also change df["Binary"] = pTraits to df["Player_Traits"] = pTraits to replace all of the values in the Player_Traits column with their respective Binary... Ouput:

    Player  Player_Traits
0   Player1          110
1   Player2          001