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I am trying to divide elements of a one column of pandas data frame with same row index elements of another column. While trying to find library functions to achieve this, I came across two functions DataFrame.div and DataFrame.divide. Their documentations are very similar and I am wondering what the differences between them might be. Are there any differences between them? Is their internal implementation different? If yes, how so? Thanks in advance.
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div() is used to find the floating division of the dataframe and other element-wise. This function is similar to dataframe/other, but with an additional support to handle missing value in one of the input data. Syntax: DataFrame.div(other, axis='columns', level=None, fill_value=None)
DataFrame elements can be divided by a pandas series or by a Python sequence as well. Calling div() on a DataFrame instance is equivalent to invoking the division operator (/). The div() method provides the fill_value parameter which is used for replacing the np.
In the pandas series constructor, the div() or divide() method is used to perform floating division of two series objects or division of a series with a scalar value. And performs element-wise division operation. The method returns a series with the result of floating division values.
The simple division (/) operator is the first way to divide two columns. You will split the First Column with the other columns here. This is the simplest method of dividing two columns in Pandas. We will import Pandas and take at least two columns while declaring the variables.
They are both aliases for the function pd.DataFrame.truediv, and they all do the same thing - perform index-aligned division along the given axis.
truediv is one of the main operations specified in the _op_descriptions data-structure in pandas/core/ops.py. div and divide are later created as references to this.
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