I am doing a comparison between Python and Julia by analyzing the same data set.
I am using a data set containing nearly 800,000 rows of data. I load the data from two csv files containing equal amount of data each and then merge them together.
I applied Random Forest algorithm to the data.
Given below is the time the python and julia code took to do the same tasks.
Loading Data: Python - 2.195s
Julia - 15.232s
Merging data: Python - 0.1505s
Julia - 5.55s
Prediction time: Python - 10.2617s
Julia - 24.5291s
Visualization: Python - 0.3434s
Julia - 35.338s
Can anyone help me in understanding why Julia is so much slower compared to Python in the above mentioned tasks.