CODEWITHSUNDEEP
pandas
shantanuo
shantanuo

Reputation: 32286

convert first row data to dictionary and remove nan values

I need to convert the first row to a dictionary and then remove all "nan" values. This works...

pd.Series(df.head(1).T.to_dict()[0]).dropna()

Or. this one...

df.head(1).dropna(axis=1).T.to_dict()[0]

But is there any other way to achive this? The type of dataframe is sparse, if that matters.

type(df)
pandas.core.sparse.frame.SparseDataFrame

I am asking because I do not think it is pythonic and I guess there must be a method to do this.

Upvotes: 0

Views: 48

Answers (1)

Haleemur Ali
Haleemur Ali

Reputation: 28303

df.iloc[0].dropna().to_dict()

is shorter and does not require any transposing.

the .iloc method returns a series when provided a single row index, which is then cleansed of null-values & converted to a dictionary.

Upvotes: 1

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