CODEWITHSUNDEEP
pythonpandasnumpy
Incognito
Incognito

Reputation: 351

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

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])

enter image description here

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

enter image description here

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?

Upvotes: 1

Views: 342

Answers (3)

danPho
danPho

Reputation: 87

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

Upvotes: 1

Irsyaduddin
Irsyaduddin

Reputation: 66

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

Upvotes: 1

Vladimir Fokow
Vladimir Fokow

Reputation: 3883

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

Upvotes: 1

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