Python3, adding varying number of columns in pandas dataframe

Question

I have a dataframe of 2 initial columns col1 and col2. I want to add more columns based on the values in a list named y. The point is len(y) is varying.

import numpy as np
import pandas as pd

class Banana:
    def __init__(self):
        self.val1 = None
        self.Val2 = None
        self.name = None

b_a = Banana()
b_b = Banana()
b_c = Banana()
bananas = list()

# step 1: data preparation
case_dependent_value = 3
v1 = 1
v2 = np.arange(case_dependent_value)

b_a.val1 = v1
b_a.val2 = v2
b_a.name = 'b_a'

b_b.val1 = v1
b_b.val2 = v2
b_b.name = 'b_b'

b_c.val1 = v1
b_c.val2 = v2
b_c.name = 'b_c'

bananas.append(b_a)
bananas.append(b_b)
bananas.append(b_c)

# step 2: make dataframe
values_1 = list()
names = list()
for each_banana in bananas:
    values_1.append(each_banana.val1)
    names.append(each_banana.names)

df = pd.DataFrame({'values_1': values_1, 'names': names})

The generated df is:

    names | values_1
0    b_a  |  1
1    b_b  |  1
2    b_c  |  1

Now I want to add the val2 of objects b_a, b_b, b_c as columns in the df. The point is the size of val2 is changing with different cases. But each case, the size is known, like the example it is 3. So the results should be

    names | values_1 | values_2_1 | values_2_2 | values_2_3
0    b_a  |   1      |    0       |     1      |   2
1    b_b  |   1      |    0       |     1      |   2
2    b_c  |   1      |    0       |     1      |   2

Could you please tell me how to achieve it? Thanks

Answer 1

If the size of the number of columns to be created is known beforehand, then you could use DF.assign() to explode the columns dynamically with the help of dictionary unpacking into it's function call as shown:

# consider a given size
size = 3
# generate column names with incremental ranges
cols = ["value_2_{}".format(item) for item in range(1,size+1)]
# map the column names and it's corresponding value to a dict object
df.assign(**dict(zip(cols, range(size))))