ValueError: setting an array element with a sequence. for Pandas

Question

I have a Pandas dataframe, called output. The basic issue is that I would like to set a certain row, column in the dataframe

Answer 1

If you really want to set a list as the value for the element, the issue is with the dtype of the column, when you create the DataFrame, the dtype gets inferred as float64 , since it only contains numeric values.

Then when you try to set a list as the value, it errors out, due to the dtype . A way to fix this would be to use a non-numeric dtype (like object) or so. Example -

output['Sold Count'] = output['Sold Count'].astype(object)
output.loc['Project1','Sold Count'] = [1000.0,800.0] #Your list

Demo -

In [91]: output = pd.DataFrame(data = [[800.0]], columns=['Sold Count'], index=['Project1'])

In [92]: output
Out[92]:
          Sold Count
Project1         800

In [93]: output['Sold Count'] = output['Sold Count'].astype(object)

In [94]: output.loc['Project1','Sold Count'] = [1000.0,800.0]

In [95]: output
Out[95]:
               Sold Count
Project1  [1000.0, 800.0]

---

You can also specify the dtype while creating the DataFrame, Example -

output = pd.DataFrame(data = [[800.0]], columns=['Sold Count'], index=['Project1'],dtype=object)
output.loc['Project1','Sold Count'] = [1000.0,800.0]

Demo -

In [96]: output = pd.DataFrame(data = [[800.0]], columns=['Sold Count'], index=['Project1'],dtype=object)

In [97]: output.loc['Project1','Sold Count'] = [1000.0,800.0]

In [98]: output
Out[98]:
               Sold Count
Project1  [1000.0, 800.0]