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% Document Info
\author{Mario (mariofreitas)}
\pdfinfo{
  /Title (python-basics-numpy-and-matplotlib.pdf)
  /Creator (Cheatography)
  /Author (Mario (mariofreitas))
  /Subject (Python Basics - Numpy and Matplotlib Cheat Sheet)
}

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\fancyhead[L]{
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
    \SetRowColor{DarkBackground}
    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Python Basics - Numpy and Matplotlib Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Mario (mariofreitas)} via \textcolor{DarkBackground}{\uline{cheatography.com/42813/cs/13226/}}}
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\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
  \SetRowColor{FootBackground}
  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}Mario (mariofreitas) \\
  \uline{cheatography.com/mariofreitas} \\
        \uline{\seqsplit{github}.com/MarioRaul/}
  \end{tabulary}
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\columnbreak
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 22nd October, 2017.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
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  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
\end{tabulary}
\end{multicols}}




\begin{document}
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% www.emerson.emory.edu/services/latex/latex_169.html
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\begin{multicols*}{2}

\begin{tabularx}{8.4cm}{x{4 cm} x{4 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Numpy - Functions}}  \tn
% Row 0
\SetRowColor{LightBackground}
`import numpy as np` & Numpy importation \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`np.sin(0)` & Returns sine of {\emph{0}} (0) \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
`np.cos(0)` & Returns cosine of {\emph{0}} (1) \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
`np.sinh(0)` & Returns hiperbolic sine of {\emph{0}} (0) \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
`np.cosh(0)` & Returns hiperbolic cosine of {\emph{0}} (1) \tn 
% Row Count 9 (+ 2)
% Row 5
\SetRowColor{white}
`np.pi` & Returns the value of {\emph{pi}} (3.1415...) \tn 
% Row Count 11 (+ 2)
% Row 6
\SetRowColor{LightBackground}
`np.array({[}1, 2, 3{]})` & Returns a 1-dimensional array \tn 
% Row Count 13 (+ 2)
% Row 7
\SetRowColor{white}
`np.array({[}{[}1, 2{]},{[}3, 4{]}{]})`\{\{nobreak\}\} & Returns a 2-dimensional array \tn 
% Row Count 15 (+ 2)
% Row 8
\SetRowColor{LightBackground}
`np.mat({[}{[}1, 2{]},{[}3, 4{]}{]})` & Returns a matrix \tn 
% Row Count 17 (+ 2)
% Row 9
\SetRowColor{white}
`np.linspace(0, 1, 11)` & Returns a 1-dimensional array from {\emph{0}} to {\emph{1}} with {\emph{11}} elements \tn 
% Row Count 21 (+ 4)
% Row 10
\SetRowColor{LightBackground}
`np.logspace(1, 3, 11)` & Returns a 1-dimensional array from {\emph{10\textasciicircum{}1\textasciicircum{}}} to {\emph{10\textasciicircum{}3\textasciicircum{}}} with 11 elements \tn 
% Row Count 25 (+ 4)
% Row 11
\SetRowColor{white}
`np.arange(0, 1, 0.1)` & Returns a 1-dimensional array from {\emph{0}} to {\emph{1}} with step {\emph{0.1}} \tn 
% Row Count 29 (+ 4)
% Row 12
\SetRowColor{LightBackground}
\seqsplit{`np.random.random((2)`} & Returns a random 1-dimensional array with 2 elements \tn 
% Row Count 32 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
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\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Numpy - Functions (cont)}}  \tn
% Row 13
\SetRowColor{LightBackground}
\seqsplit{`np.random.random((2}, 2))` & Returns a random 2-dimensional array with 2 rows and 2 columns \tn 
% Row Count 4 (+ 4)
% Row 14
\SetRowColor{white}
\seqsplit{`np.random.random((2}, 2, 2))`\{\{nobreak\}\} & Returns a random 3-dimensional array with 2 elements in each dimension \tn 
% Row Count 8 (+ 4)
% Row 15
\SetRowColor{LightBackground}
`np.eye(5)` & Returns a 5x5 identity matrix \tn 
% Row Count 10 (+ 2)
% Row 16
\SetRowColor{white}
`np.zeros(5)` & Returns a null vector with 5 elements \tn 
% Row Count 12 (+ 2)
% Row 17
\SetRowColor{LightBackground}
`np.zeros((5, 2))` & Returns a null matrix with 5 rows and 2 columns \tn 
% Row Count 15 (+ 3)
% Row 18
\SetRowColor{white}
`np.ones(5)` & Returns a 5 elements vector filled with 1 \tn 
% Row Count 18 (+ 3)
% Row 19
\SetRowColor{LightBackground}
`np.ones((5, 2))` & Returns a 5x2 matrix filled with 1 \tn 
% Row Count 20 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{8.4cm}}{\textasciicircum{}1\textasciicircum{}Numpy has all functions and constants in the library Math. \newline \textasciicircum{}2\textasciicircum{}Numpy arrays can be used to do all sorts of linear algebra calculations since they are treated as mathematical tensors (vectors and matrices) rather than Python lists. \newline \textasciicircum{}3\textasciicircum{}Numpy matrices are a special type of array that is easier to use in common linear algebra problems. Matrices are always 2D}  \tn 
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\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Numpy - Linalg}}  \tn
% Row 0
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`np.linalg.dot(a, b)` & Returns the dot product between arrays {\emph{a}} and {\emph{b}} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\seqsplit{`np.linalg.matmul(a}, b)`\{\{nobreak\}\} & Returns the matrix product between arrays {\emph{a}} and {\emph{b}} \tn 
% Row Count 6 (+ 3)
% Row 2
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\seqsplit{`np.linalg.eigvals(a)`} & Returns the eigenvalues of the square array {\emph{a}} \tn 
% Row Count 9 (+ 3)
% Row 3
\SetRowColor{white}
\seqsplit{`np.linalg.eig(a)`} & Returns the eigenvalues and eigenvectors of the square array {\emph{a}} \tn 
% Row Count 13 (+ 4)
% Row 4
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\seqsplit{`np.linalg.norm(a)`} & Returns the {\emph{a}} array norm \tn 
% Row Count 15 (+ 2)
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\seqsplit{`np.linalg.det(a)`} & Returns the determinant of {\emph{a}} \tn 
% Row Count 17 (+ 2)
% Row 6
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\seqsplit{`np.linalg.inv(a)`} & Returns the inverse of {\emph{a}} \tn 
% Row Count 19 (+ 2)
% Row 7
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\seqsplit{`np.linalg.pinv(a)`} & Returns the pseudo-inverse of {\emph{a}} \tn 
% Row Count 21 (+ 2)
% Row 8
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\seqsplit{`np.linalg.solve(a}, b)`\{\{nobreak\}\} & Returns the solution of {\emph{aX = b}} \tn 
% Row Count 23 (+ 2)
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\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
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\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Numpy - Slicing}}  \tn
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\mymulticolumn{1}{x{8.4cm}}{import numpy as np \newline  \newline a = np.array({[}{[}1, 2, 3{]}, {[}4, 5, 6{]}, {[}7, 8, 9{]}{]}) \newline a{[}1:, 1:{]} = {[}{[}50, 60{]}, {[}80, 90{]}{]} \newline print(a)} \tn 
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\mymulticolumn{1}{x{8.4cm}}{{[}{[} 1  2  3{]} \newline  {[} 4 50 60{]} \newline  {[} 7 80 90{]}{]}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\begin{tabularx}{8.4cm}{X}
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\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Matplotlib - Example}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{from matplotlib import pyplot as plt \newline import numpy as np \newline  \newline x = np.linspace(0, 10, 200) \newline y1 = 3{\emph{np.sin(x) + np.cos(x) \newline y2 = 2}}np.cos(x) - np.sin(x) \newline  \newline plt.plot(x, y1, '-b', label="y1") \newline plt.plot(x, y2, '-r', label="y2") \newline plt.xlabel("x") \newline plt.ylabel("y") \newline plt.title("Y Vs. X") \newline plt.legend() \newline plt.grid() \newline plt.show()} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\begin{tabularx}{8.4cm}{X}
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\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Matplotlib - Example (Output)}}  \tn
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\mymulticolumn{1}{p{8.4cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/mariofreitas_1508696670_Figure_1.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\begin{tabularx}{8.4cm}{x{4.24 cm} x{3.76 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Matplotlib - Pyplot Functions}}  \tn
% Row 0
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`from matplotlib import pyplot as plt`\{\{nobreak\}\} & Pyplot importation \tn 
% Row Count 3 (+ 3)
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`plt.plot(x, y{[},args{]})` & Plots {\emph{x}} Vs. {\emph{y}} on current figure \tn 
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\SetRowColor{LightBackground}
`plt.xlabel("x")` & Sets x-axis label to {\emph{x}} \tn 
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`plt.ylabel("y")` & Sets y-axis label to {\emph{y}} \tn 
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`plt.title("Y Vs. X")` & Sets figure title to {\emph{Y Vs. X}} \tn 
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`plt.legend()` & Shows legends in figure \tn 
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`plt.grid()` & Shows grid in figure \tn 
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`plt.show()` & Shows figures \tn 
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`plt.figure()` & Starts a new figure \tn 
% Row Count 18 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{8.4cm}}{\textasciicircum{}1\textasciicircum{} Many args can be set on {\emph{plt.plot()}}. Some are shown on the next block.}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{p{1.28 cm} x{6.72 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Pyplot - Lines, Markers and Colors}}  \tn
% Row 0
\SetRowColor{LightBackground}
'-' & solid line style \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
'-{}-' & dashed line style \tn 
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\SetRowColor{LightBackground}
'-.' & dash-dot line style \tn 
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\SetRowColor{white}
':' & dotted line style \tn 
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'.' & point marker \tn 
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',' & pixel marker \tn 
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'o' & circle marker \tn 
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'v' & triangle\_down marker \tn 
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'\textasciicircum{}' & triangle\_up marker \tn 
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'\textgreater{}' & triangle\_right marker \tn 
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's' & square marker \tn 
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'p' & pentagon marker \tn 
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'*' & star marker \tn 
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'h' & hexagon1 marker \tn 
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'b' & blue \tn 
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'g' & green \tn 
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'r' & red \tn 
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'c' & cyan \tn 
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'm' & magenta \tn 
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'y' & yellow \tn 
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'k' & black \tn 
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'w' & white \tn 
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\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{8.4cm}}{You can use a line style, a marker and a color directly at plt.plot() like this: \newline `plt.plot(x, y, '-+b')`}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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% That's all folks
\end{multicols*}

\end{document}