Python: Loop through tuple and insert into Data Frame for each value

Question

Trying to loop through the tuple that is currently a column in my data frame. For the first ID I want to select the first item in the group tuple then for the second ID select the second variable in the tuple. For the remaining ID’s in the same group I would like to cycle back through the tuple.

If the group changes I would like to repeat the process with the new group. I’m also fine with splitting it into a new data frame and then union the results back in later.

df = pd.DataFrame({'ID':[1,2,3,4,5,6],
                   'Group':["('Cat','Dog')",
                             "('Cat','Dog')",
                             "('Cat','Dog')",
                             "('Cat','Dog')",
                             "('Bird','Dog')",
                             "('Bird','Dog')",                             
                            ]
                  })

ID	Group
1	(‘Cat’, ‘Dog’)
2	(‘Cat’, ‘Dog’)
3	(‘Cat’, ‘Dog’)
4	(‘Cat’, ‘Dog’)
5	(‘Bird’, ‘Dog’)
6	(‘Bird’, ‘Dog’)

ID	Group
1	Cat
2	Dog
3	Cat
4	Dog
5	Bird
6	Dog

Asked By: Shell Shock

||

Source

Answer 1

Assuming a column of tuples:

df['Group'] = (df.groupby(df['ID'].sub(1).mod(2))['Group']
                 .transform(lambda s: s.str[s.name])
               )

If you have strings:

from ast import literal_eval
df['Group'] = (df['Group'].apply(literal_eval)
               .groupby(df['ID'].sub(1).mod(2))
               .transform(lambda s: s.str[s.name])
              )

Output:

   ID Group
0   1   Cat
1   2   Dog
2   3   Cat
3   4   Dog
4   5  Bird
5   6   Dog

Answered By: mozway

Answer 2

Just do this

# Using lambda function we apply eval() to evaluate arbitrary expressions from a string-based input
df['Group'] = df['Group'].apply(lambda x: eval(x)) 

# Here we loop through and insert the values into the dataframe
df['Group'] = df.apply(lambda x: x['Group'][x['ID'] % 2 == 0], axis=1)

Answered By: Pratik Bhadane

Answer 3

# Create a copy of the original dataframe and assign it to temp_df
temp_df = df.copy()

# Explode the 'Group' column in the temp_df dataframe
temp_df = temp_df.explode('Group').reset_index(drop=True)

# Strip the brackets and split the values in the 'Group' column
temp_df['Group'] = temp_df['Group'].str.strip("()").str.split(",")

# Explode the 'Group' column again to create one row per value
temp_df = temp_df.explode('Group').reset_index(drop=True)

# Strip the single quotes from the values in the 'Group' column
temp_df['Group'] = temp_df['Group'].str.strip("'")

# Print the modified temp_df dataframe
print(temp_df)

Answered By: Carlos BL

Python: Loop through tuple and insert into Data Frame for each value

Question:

Answers: