CSV format data manipulation: why use python scripts instead of MS excel functions?
Using python is recommended for below scenarios:

Repeated action: Perform similar set of action over a similar dataset repeatedly. For ex, say you get a monthly forecast data and you have to perform various slicing & dicing and plotting. Here the structure of data and the steps of analysis is more or less the same, but the data differs for every month. Using Python and Pandas will save you a bulk of time and also reduces manual error.
Exploratory analysis: Once you establish a certain familiarity with Pandas, Numpy and Matplotlib, analysis using these python libraries are faster and much efficient than Excel Analysis. One simple usecase to justify this statement is backtracking. With Pandas, you can quickly trace back and regain the dataset to its original form or an earlier analysed form. With Excel, you could get lost after a maze of analysis, and might be in a lose of backtrack to an earlier form outside of cntrl + z
Teaching Tool: In my opinion, this is the most underutilized feature. IPython notebook could be an excellent teaching tool and reference document for data analysis. Using this, you can efficiently transfer knowledge between colleagues rather than sharing a complicated excel file.
I am currently working on large data sets in csv format. In some cases, it is faster to use excel functions to get the work done. However, I want to write python scripts to read/write csv and carry out the required function. In what cases would python scripts be better than using excel functions for data manipulation tasks? What would be the long term advantages?