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pandas df.loc[conditions] – Failed to convert data from binary format

Python novice here. I’m using the pandas.Dataframe.loc[conditions] method. When I run the code below, I get the error

Failed to convert column 1 from string to float: Insufficient precision
for float

Here is the code that goes with it
#tensor columns
df_wgt[‘Weights’] = df_wgt.iloc[:, :-2].astype(float)

#Get the weights into a list
wgt_list = df_wgt.loc[df_wgt[‘Tensor’] == ‘concat’].Weights.tolist()

#print the list
print(wgt_list)

#Find the indexes of the 1’s in the list
wgt_i = np.where(wgt_list == 1.0)[0]

#Apply the weights
df_wgt[‘WeightedInput’] = df_wgt.iloc[:, :-2].astype(float).apply(lambda x: wgt_list[wgt_i], axis=1)

#Print the new values and error message
print(df_wgt)

I know that the problem has to do with a data type, but I can’t figure out what to do about it. Any help would be appreciated.

The problem is a few values in your initial Weights column are NaN. You can check this by:
print(np.any(df_wgt[‘Weights’]!= np.nan, axis=1))

In this case, the result is False. You need to substitute any NaN with 0 before doing your conversions or other computations.
I was able to reproduce the error with the following code:
df_wgt[‘Weights’] = df_wgt.iloc[:, :-2].astype(float)
df_wgt[‘Weights’] = df_wgt[‘Weights’].fillna(0)
df_wgt[‘Weighted
50b96ab0b6

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#include
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void
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{
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