Converting a list with some nested list elements and tuples to a dataframe

Question

The list that I want to convert into a dataframe stores different data types in each cell:

[In]  type(example_list)
[Out] list

[In]  type(example_list[0])
[Out] list

[In]  type(example_list[0][0])
[Out] str

[In]  type(example_list[0][1])
[Out] tuple

[In]  type(example_list[0][2])
[Out] tuple

[In]  type(example_list[0][1][0])
[Out] list

And the tuple elements all have the following format:

[In]  example_list[0][1]
[Out] ([array([200.85183333, 200.85183333, 200.85183333])], ['#c8c8c8'])

[In] type(example_list[0][1][0])
[Out] list

[In] type(example_list[0][1][1])
[Out] list

When I use the pd.DataFrame function I end up with 3 columns, but I want to have 5 columns (that is, 2 columns from each tuple element).

When I run the following command:

df = pd.DataFrame(example_list, columns=['Name','PrimaryColors','SecondaryColors'])
df.to_csv('test.csv', sep=',')

This is what I get (outputting only the first row below):

E123    ([array([200.85183333, 200.85183333, 200.85183333])], ['#c8c8c8'])  ([array([226.9, 226.9, 226.9])], ['#e2e2e2'])

How can I instead end up with 5 columns instead of 3 and have the dataframe follow the following format?

Name    PrimaryColorRGB                             PrHEX       SecondaryColorsRGB       SecHEX
E123    200.85183333, 200.85183333, 200.85183333    #c8c8c8     226.9, 226.9, 226.9      #e2e2e2

1. Sorry, but this way the structure of your input list is not clear to me. 2. Where does this input originate from - could you adjust or change it to be processed better into a dataframe? — SpghttCd
– SpghttCd, Commented Jan 31, 2020 at 9:49

SpghttCd · Accepted Answer · 2020-01-31 14:21:30Z

1

Iiuc, you can create your desired result from your 3-column-dataframe according to jezrael's answer to a similar question here: https://stackoverflow.com/a/35491399/8300135

In your case:

df[['PrimaryColorsRGB','PrimaryColorsHex']] = pd.DataFrame(df.PrimaryColors.values.tolist(), index= df.index)

The same with your secondary colors column.

However, in your case you still get column entries which are lists with only one element, a tuple in one column and a string in the other.

You could address this issue like

df.PrimaryColorsRGB = df.PrimaryColorsRGB.str[0]
df.PrimaryColorsHex = df.PrimaryColorsHex.str[0]

Again, the same with secondary colors columns.

answered Jan 31, 2020 at 14:21

SpghttCd

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