Convert missing values in a DataFrame to a given data type (Python - Pandas)

Question

I have a DataFrame d1 with strings and missing values, such as

d1 = pd.DataFrame([["A", "B", "C"],
                   ["D", np.nan, "F"],
                   ["G", "H", "I"],],
                  columns=[1, 2, 3])

whose columns I would like to aggregate in single-row DataFrame d2:

Folllowing suggestions in a previous post, tried the following code:

d2 = d1.agg(''.join).to_frame().T

Still, as one of the values in d1 was missing (and, thus, a float), I got the following error:

TypeError: sequence item 1: expected str instance, float found

Would you know how to change missing values in DataFrames to another data type such as string?

Does this answer your question? Pandas dataframe fillna() only some columns in place — Vladimir Fokow
– Vladimir Fokow, Commented Aug 27, 2022 at 0:04

Vladimir Fokow · Accepted Answer · 2022-08-27 00:03:45Z

1

You can fill the missing value with an empty string:

d1.fillna('')

So the overall code becomes

d1.fillna('').agg(''.join).to_frame().T

     1   2    3
0  ADG  BH  CFI

answered Aug 27, 2022 at 0:03

Vladimir Fokow

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Comments

Irsyaduddin · Accepted Answer · 2022-08-27 00:10:17Z

1

You can do a replace for nan values into ''

d1 = pd.DataFrame([["A", "B", "C"],
                   ["D", np.nan, "F"],
                   ["G", "H", "I"],],
                  columns=['1', '2', '3'])
d1.replace(np.nan,'',inplace=True)
d2 = d1.agg(''.join,axis=1).to_frame().T

answered Aug 27, 2022 at 0:10

Irsyaduddin

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Comments

danPho · Accepted Answer · 2022-08-27 00:47:15Z

1

The null value is causing the error, so fill it with empty string. You could try this:

d2 = pd.DataFrame(d1.fillna('').agg(''.join)).T
print(d2)

     1   2    3
0  ADG  BH  CFI

answered Aug 27, 2022 at 0:47

danPho

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