dataframe row as into numpy array

Question

I have a dataframe, columns to be used are "sepal_length" and "sepal_width". I want to turn each single row into a single data point, like point1= [5.1 3.5] and point2 = [4.9 3] and so on. .to_numpy() just turns the whole 2 columns into large-sized numpy array, so it does not work for me. How can I work out?

does this solve your problem stackoverflow.com/questions/13187778/… — Joe Ferndz
– Joe Ferndz, Commented Oct 30, 2020 at 6:35
Does this answer your question? Mapping rows of a Pandas dataframe to numpy array — Ruli
– Ruli, Commented Oct 30, 2020 at 6:37

Qamar Abbas · Accepted Answer · 2020-10-30 07:12:31Z

0

You can simply use this:

nump_df=df.values
print(nump_df)

or

You can iterate over rows and convert each row to numpy array and append those arrays in a list. I hope the following code will help you:

point=[]
for idx, row in df.iterrows():
    p=row.to_numpy()
    point.append(p)

print(point)

edited Oct 30, 2020 at 7:12

answered Oct 30, 2020 at 7:07

Qamar Abbas

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