[youtube https://www.youtube.com/watch?v=LSxqpaCCPvY?rel=0]

Pandas is a Python library developed by Wes McKinney. The USP of Pandas is that it provides “Data Frame” environment in Python. Dataframe is one of the commonly used data structures in R. The first thing that pains you when you start coding in Python , after having worked in R is that – “there is no readily available data frame object” . Even though there is NumPy ndarray object, it is not as flexible and extensible as the dataframe in R.

Via Mint : Announcing the long-awaited guidelines for so-called algorithmic trading, or “algo” as it’s popularly known, India’s capital market regulator on Friday insisted on a stringent and advanced risk management system to provide support for such trades as their speed and volume entail a higher risk. Automated execution logic enables the rapid execution of a large number of trade orders. Stock exchanges have been given three months to complete the approval process for brokers currently executing orders through algos.

For any number crunching work, be it making a report or developing a model or doing data diagnostics, visualization of the data is imperative. Be it univariate or multivariate data, visuals help us to look beyond the summary statistics or test statistics. For someone working in finance, there is an entire discipline of `Technical Trading' where buy , sell , stop-loss decisions are made based on visuals. Whether one believes it or not is a different question altogether.

Talent borrows, genius steals - Oscar Wilde