CODEWITHSUNDEEP
python-3.xpandas
anarz
anarz

Reputation: 209

Getting a dataframe of combinations from a list of dictionaries

I have a following list of dictionaries:

options = [{'A-1': ['x', 'y']},
           {'A-3': ['x', 'y', 'z']},

Values of each dictionary (e.g. x and y) are basically the options that keys (e.g. A-1) can have. How can I have the following dataframe of combinations? Only one value (e.g. either x or y) of a key (e.g. A-1) can can take 1 at a time. All values of a dictionary cannot be 0 at a time.

I have trying to use itertools.combinations(), but couldn't find the way to get the desired result.

enter image description here

This way I can find the number of combinations n_comb and number of connections n_conn which will be number of rows and columns of the dataframe.

n_conn = 0
n_comb = 1
for dic in options:
    for key in dic:
        n_comb = n_comb * len(dic[key])
        n_conn = n_conn + len(dic[key])

Upvotes: 3

Views: 67

Answers (1)

Chris
Chris

Reputation: 29742

One way using pandas.get_dummies and merge:

dfs = [pd.get_dummies(pd.DataFrame(o)).assign(merge=1) for o in options]
new_df = dfs[0].merge(dfs[1], on="merge").drop("merge", 1)
print(new_df)

Or make it more flexible using functools.reduce:

from functools import reduce

new_df = reduce(lambda x, y: x.merge(y, on="merge"), dfs).drop("merge", 1)

Output:

   A-1_x  A-1_y  A-3_x  A-3_y  A-3_z
0      1      0      1      0      0
1      1      0      0      1      0
2      1      0      0      0      1
3      0      1      1      0      0
4      0      1      0      1      0
5      0      1      0      0      1

Upvotes: 2

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