One way to transform a list within a dataframe to a binary data type is to use the get_dummies()
function from the pandas library. This function will create binary columns for each unique value in the list. Here is an example:
import pandas as pd
# create a sample dataframe with a list column
df = pd.DataFrame({'A': [1, 2, 3],
'B': [['apple', 'banana'], ['orange', 'banana'], ['apple', 'orange']]})
# transform the list column to binary data type
df = pd.concat([df.drop('B', axis=1), pd.get_dummies(df['B'].apply(pd.Series).stack()).sum(level=0)], axis=1)
print(df)
Output:
A apple banana orange
0 1 1 1 0
1 2 0 1 1
2 3 1 0 1
In this example, the get_dummies()
function is applied to the 'B' column and the resulting binary columns are concatenated with the other columns in the dataframe. The resulting dataframe has binary columns for each unique value in the list.
Please start posting anonymously - your entry will be published after you log in or create a new account. This space is reserved only for answers. If you would like to engage in a discussion, please instead post a comment under the question or an answer that you would like to discuss
Asked: 2021-09-11 11:00:00 +0000
Seen: 14 times
Last updated: Jan 25 '23
How do you update a dataframe within a for loop in R after passing a list?
How can we bring googlesheets data into a pyspark dataframe?
How can a portion of a file name be retrieved and stored in a DataFrame using Pandas?
How can we perform aggregate functions on particular datetime values in a Pandas DataFrame?
How can you display a Pandas Dataframe using a for loop?
What is the method for computing the overall sum of a dataframe, excluding a singular row?
What is the method for making a struct in a Spark dataframe less complex?