\documentclass[12pt]{article}

\title{Interactive Plotting}

\author{FOSSEE}

\begin{document}

\date{}

\vspace{-1in}

\begin{center}

\LARGE{Statistics and Least square fit}\\

\large{FOSSEE}

\end{center}

\section{Statistics}

Dictionary

\begin{verbatim}

In [1]: d = {"Hitchhiker's guide" : 42, 

  ....:      "Terminator" : "I'll be back"} #Creation

In [2]: d["Hitchhiker's guide"] # Accessing a value with key

In [3]: "Hitchhiker's guide" in d #Checking for a key

In [4]: d.keys() # Obtaining List of Keys

In [5]: d.values() # Obtaining List of Values

\end{verbatim}

Iterating through List indices

\begin{verbatim}

In [1]: names = ["Guido","Alex", "Tim"]

In [2]: for i, name in enumerate(names):

   ...:     print i, name

\end{verbatim}

\begin{verbatim}

In [1]: score = int(score_str) if score_str != 'AA' else 0

\end{verbatim}

Drawing Pie Charts

\begin{verbatim}

In [1]: pie(science.values(), labels=science.keys())

\end{verbatim}

sum() and len() functions

\begin{verbatim}

In [1]: mean = sum(math_scores) / len(math_scores)

\end{verbatim}

Numpy Arrays

\begin{verbatim}

In [1]: a = array([1, 2, 3]) #Creating

In [2]: b = array([4, 5, 6])

In [3]: a + b #Sum; Element-wise

\end{verbatim}

Numpy statistical operations 

\begin{verbatim}

In [1]: mean(math_scores)

In [2]: median(math_scores)

In [3]: stats.mode(math_scores)

In [4]: std(math_scores)

\end{verbatim}

Generating Van der Monde matrix

\begin{verbatim}

In [1]: A = vander(L, 2)

\end{verbatim}

Getting a Least Squares Fit curve

\begin{verbatim}

In [1]: coef, res, r, s = lstsq(A,TSq)

In [2]: Tline = coef[0]*L + coef[1]

In [3]: plot(L, Tline)

\end{verbatim}

\end{document}