如何用特定的dtype创建一个新的空熊猫列？

Question

I have a DataFrame df with columns 'a' . How would I create a new column 'b' which has dtype=object ?

I know this may be considered poor form, but at the moment I have a dataframe df where the column 'a' contains arrays (each element is an np.array ). I want to create a new column 'b' where each element is a new np.array that contains the logs of the corresponding elemnent in 'a' .

At the moment I tried these two methods, but neither worked:

    for i in df.index:
        df.set_value(i,'b', log10(df.loc[i,'a']))

and

    for i in df.index:
        df.loc[i,'b'] = log10(df.loc[i,'a']))

Both give me ValueError: Must have equal len keys and value when setting with an iterable .

I'm assuming the error comes about because the dtype of the new column is defaulted to float although I may be wrong.

Answer 1

As each row of your column is an array, it's better to use the standard NumPy mathematical functions for computing their element-wise logarithms to the base 10:

df['log_a'] = df.a.apply(lambda x: np.log10(x))