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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
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% Document Info
\author{Taissir Boukrouba (taissir2002)}
\pdfinfo{
  /Title (numpy-cheat-sheet.pdf)
  /Creator (Cheatography)
  /Author (Taissir Boukrouba (taissir2002))
  /Subject (Numpy 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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\end{tabulary}
\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Numpy Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Taissir Boukrouba (taissir2002)} via \textcolor{DarkBackground}{\uline{cheatography.com/193976/cs/40715/}}}
\end{tabulary}
\end{multicols}}

\fancyfoot[L]{ \footnotesize
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
  \SetRowColor{FootBackground}
  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}Taissir Boukrouba (taissir2002) \\
  \uline{cheatography.com/taissir2002} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 8th November, 2023.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
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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}
\raggedright
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\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{x{2.68758 cm} x{2.28942 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{Creating Arrays}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Create simple array}} & np.array({[}list{]}) \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
{\bf{Array filled with zeros}} & np.zeros(size) \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
{\bf{Array filled with ones}} & np.ones(size) \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
{\bf{Array filled with a number}} & np.full(size,number) \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
{\bf{Array from a range of numbers (last not included)}} & np.arange(start,stop,step) \tn 
% Row Count 11 (+ 3)
% Row 5
\SetRowColor{white}
{\bf{Array from a range of numbers (last included)}} & np.linspace(start,stop,count) \tn 
% Row Count 14 (+ 3)
% Row 6
\SetRowColor{LightBackground}
{\bf{Array filled with random numbers (float)}} & \seqsplit{np.random.random(size)} \tn 
% Row Count 17 (+ 3)
% Row 7
\SetRowColor{white}
{\bf{Array filled with random numbers (int)}} & \seqsplit{np.random.randint(start},stop,size) \tn 
% Row Count 19 (+ 2)
% Row 8
\SetRowColor{LightBackground}
{\bf{Create identity Matrix}} & np.eye(k) \tn 
% Row Count 21 (+ 2)
% Row 9
\SetRowColor{white}
{\bf{Create empty Matrix}} & np.empty(k) \tn 
% Row Count 23 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{Size can be the following :  \newline {\bf{ 1) one-dimensional (Array)}} : where size = k = (k) \newline {\emph{eg : np.zeros(2) , creates an array of 2 elements}} \newline {\bf{2) two-dimensional (Matrix)}} : where size = (a,b) \newline {\emph{eg : np.zeros((2,3)) , creates a matrix of 2 rows and one column}} \newline {\bf{ 3) n-dimensional }} : where size = (a,b,c....etc) \textgreater{} 2  \newline {\emph{eg : np.zeros((2,3,5)) , creates a 3 dimensional array}}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.55618 cm} x{1.51041 cm} x{1.51041 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Reading Array From Text File}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Inspecting the file (without reading it)}} & !head file\_source & !head \seqsplit{data/array\_float}.csv \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
{\bf{Loading File Into Array}} & \seqsplit{np.loadtxt(source}, delimiter, dtype) & B = \seqsplit{np.loadtxt("data/array\_int.csv"}, delimiter = ",", dtype=int) \tn 
% Row Count 9 (+ 5)
% Row 2
\SetRowColor{LightBackground}
{\bf{Loading Array Into File}} & \seqsplit{np.savetxt(source}, array, fmt ,delimiter) & \seqsplit{np.savetxt("data/my\_array.csv"}, B, fmt="\%3i", delimiter=",") \tn 
% Row Count 14 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{{\emph{Make sure that you are typing the right datatype of the text file or you will receive an error}} \newline  \newline The {\bf{fmt}} keyword is used to specify the spacing in our text file where :  \newline - `fmt = "\%3i"` means 3 spaces between row elements (numbers are integers) \newline - `fmt = "\%5.1i"` means 5 spaces between row elements and only one number after floating point}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{3.68298 cm} x{1.29402 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{Numpy Array Attributes}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Returns number of dimensions}} & \seqsplit{array.ndim} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
{\bf{Returns size of each dimension}} & \seqsplit{array.shape} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
{\bf{Returns number of elements}} & \seqsplit{array.size} \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
{\bf{Returns type of elements}} & \seqsplit{array.dtype} \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
{\bf{Returns size of each element in bytes}} & \seqsplit{array.itemsize} \tn 
% Row Count 10 (+ 2)
% Row 5
\SetRowColor{white}
{\bf{Returns size of all elements in bytes}} & \seqsplit{array.nbytes} \tn 
% Row Count 12 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.60195 cm} x{1.69349 cm} x{1.28156 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Array Indexing}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Accessing array element}} & array\_name{[}index{]} & x1{[}5{]} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
{\bf{Modify array element}} & array\_name{[}index{]} = new\_value & x1{[}5{]} = 69 \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
{\bf{Accessing matrix element}} & matrix\_name{[}row,column{]} & x2{[}2, -1{]} \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
{\bf{Modify matrix element}} & matrix\_name{[}row,column{]} = new\_value & x2{[}2, -1{]} = -5 \tn 
% Row Count 10 (+ 3)
% Row 4
\SetRowColor{LightBackground}
{\bf{Accessing sub-arrays}} & array\_name{[}start,stop,step=1{]} & x{[}1:5{]} \{\{nl\}\} x{[}1:5:3{]} \tn 
% Row Count 13 (+ 3)
% Row 5
\SetRowColor{white}
{\bf{Accessing multi-dim arrays}} & array\_name{[}row\_range,column\_range{]} & x2{[}::-1, ::-1{]} \tn 
% Row Count 16 (+ 3)
% Row 6
\SetRowColor{LightBackground}
{\bf{Creating subarrays as no-copy views}} & sub\_array = original\_array{[}slice{]} & x2\_sub = x2{[}:2, :2{]} \tn 
% Row Count 19 (+ 3)
% Row 7
\SetRowColor{white}
{\bf{Creating subarrays as copy views}} & sub\_array = original\_array{[}slice{]}.copy() & \seqsplit{x2\_sub\_copy} = x2{[}:2, :2{]}.copy() \tn 
% Row Count 22 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{We can access multiple matrix rows and columns when both row and columns are lists :  \newline  \newline x2{[}{[}1,2{]},{[}1,1{]}{]} -\textgreater{} this means access \# Second and Third row ({[}1,2{]}) , Second and Second column}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.96811 cm} x{1.46464 cm} x{1.14425 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Reshaping of Arrays}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Reshape array}} & \seqsplit{array.reshape((rows},columns)) & x2 = \seqsplit{x1.reshape((3}, 3)) \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
{\bf{Reshape into row vector}} & \seqsplit{array.reshape((1},columns)) & x2 = \seqsplit{x1.reshape((1}, 3)) \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
{\bf{Reshape into row vector using np.newaxis}} & array{[}np.newaxis, :{]} & x2 = x1{[}np.newaxis, :{]} \tn 
% Row Count 9 (+ 3)
% Row 3
\SetRowColor{white}
{\bf{Reshape into column vector}} & \seqsplit{array.reshape((rows},1)) & x2 = \seqsplit{x1.reshape((3}, 1)) \tn 
% Row Count 12 (+ 3)
% Row 4
\SetRowColor{LightBackground}
{\bf{Reshape into column vector using np.newaxis}} & array{[}:, np.newaxis{]} & x2 = x1{[}:, np.newaxis{]} \tn 
% Row Count 15 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{{\bf{It is very important to note that number of rows multiplied by the number of columns must be equal to the number of array elements}}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.60195 cm} x{1.60195 cm} x{1.3731 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Array Concatenation and Splitting}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Concatenate Arrays vertically (default)}} & np.concatenate({[}x1,x2,x3....{]}) & np.concatenate({[}x, y{]}) \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
{\bf{Concatenate Arrays horizontally}} & np.concatenate({[}x1,x2,x3....{]} , axis=1) & np.concatenate({[}x, y{]}, axis=1) \tn 
% Row Count 7 (+ 3)
% Row 2
\SetRowColor{LightBackground}
{\bf{Stack Arrays vertically}} & np.vstack({[}x1, x2,x3....{]}) & np.vstack({[}x, y{]}) \tn 
% Row Count 9 (+ 2)
% Row 3
\SetRowColor{white}
{\bf{Stack Arrays horizontally}} & np.hstack({[}x1, x2,x3....{]}) & np.hstack({[}x, y{]}) \tn 
% Row Count 12 (+ 3)
% Row 4
\SetRowColor{LightBackground}
{\bf{Spliting Arrays}} & \seqsplit{np.split(array}, {[}first\_split\_point, \seqsplit{second\_split\_point} , \seqsplit{third\_split\_point}....{]}) & x1, x2, x3 = np.split(x, {[}3, 5{]}) \tn 
% Row Count 18 (+ 6)
% Row 5
\SetRowColor{white}
{\bf{Splitting Matrixes vertically}} & \seqsplit{np.vsplit(matrix}, {[}frist\_row\_index,second\_row\_index....{]}) & upper, lower = \seqsplit{np.vsplit(grid}, {[}2{]}) \tn 
% Row Count 23 (+ 5)
% Row 6
\SetRowColor{LightBackground}
{\bf{Splitting Matrixes horizontally}} & \seqsplit{np.hsplit(matrix}, {[}frist\_col\_index,second\_col\_index....{]}) & left, right = \seqsplit{np.hsplit(grid}, {[}2{]}) \tn 
% Row Count 28 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{{\bf{NOTE :}} \newline {\bf{concatenate or stack vertically :}} must have same number of columns \newline {\bf{concatenate or stack horizontally :}} must have same number of rows \newline  \newline {\bf{NOTE 2 :}} \newline The number of split points when splitting an array depends on the number of arrays generated where :  \newline {\emph{Number of split points = number of arrays outputted - 1}} \newline  \newline `x1, x2, x3 = np.split(x, {[}3, 5{]})` -\textgreater{} split on the third element to x1 , split on the fifth element to x2 (from forth element) , give the rest to x3}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.19002 cm} x{1.92234 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Numpy Operations \& UFuncs}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Addition}} & Array + number & x = {[}0 1 2 3{]}\{\{nl\}\} x+5 \{\{nl\}\} {\emph{output : {[}5 6 7 8{]}}} \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
{\bf{Substraction}} & Array - number & x = {[}5 6 7 8{]}\{\{nl\}\} x-5 \{\{nl\}\} {\emph{output : {[}0 1 2 3{]}}} \tn 
% Row Count 8 (+ 4)
% Row 2
\SetRowColor{LightBackground}
{\bf{Multiplication}} & Array * number & x*2 \{\{nl\}\} {\emph{output : {[}0 2 4 6{]}}} \tn 
% Row Count 10 (+ 2)
% Row 3
\SetRowColor{white}
{\bf{Division}} & Array / number & x/2 \{\{nl\}\} {\emph{output : {[}0,0.5,1,1.5{]}}} \tn 
% Row Count 13 (+ 3)
% Row 4
\SetRowColor{LightBackground}
{\bf{Floor Division}} & Array // number & x//2 \{\{nl\}\} {\emph{output : {[}0,0,1,1{]}}} \tn 
% Row Count 15 (+ 2)
% Row 5
\SetRowColor{white}
{\bf{Exponential}} & Array ** number & x{\emph{*2 \{\{nl\}\} }}output : {[}0 1 4 9{]}* \tn 
% Row Count 17 (+ 2)
% Row 6
\SetRowColor{LightBackground}
{\bf{Modulus}} & Array \% number & x \% 2 \{\{nl\}\} {\emph{output : {[}0 1 0 1{]}}} \tn 
% Row Count 20 (+ 3)
% Row 7
\SetRowColor{white}
{\bf{Dot Multiplication}} & matrix1 @ matrix2 & check the notes \tn 
% Row Count 22 (+ 2)
% Row 8
\SetRowColor{LightBackground}
{\bf{UFunc Addition}} & \seqsplit{np.add(array},number) & np.add(x,5)\{\{nl\}\} {\emph{output : {[}5 6 7 8{]}}} \tn 
% Row Count 25 (+ 3)
% Row 9
\SetRowColor{white}
{\bf{UFunc Substraction}} & \seqsplit{np.subtract(array},number) & np.subtract(x,5)\{\{nl\}\} {\emph{output : {[}0 1 2 3{]}}} \tn 
% Row Count 28 (+ 3)
% Row 10
\SetRowColor{LightBackground}
{\bf{UFunc Multiplication}} & \seqsplit{np.multiply(array},number) & np.multiply(x,2)\{\{nl\}\} {\emph{output : {[}0 2 4 6{]}}} \tn 
% Row Count 31 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.19002 cm} x{1.92234 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Numpy Operations \& UFuncs (cont)}}  \tn
% Row 11
\SetRowColor{LightBackground}
{\bf{UFunc Dot}} & \seqsplit{np.dot(matrix1},matrix2) & check the notes \tn 
% Row Count 3 (+ 3)
% Row 12
\SetRowColor{white}
{\bf{UFunc Absolute Value}} & np.abs(x) & x = np.array({[}-2, -1, 0, 1, 2{]})\{\{nl\}\}np.abs(x)\{\{nl\}\}{\emph{output : {[}2,1,0,1,2{]}}} \tn 
% Row Count 8 (+ 5)
% Row 13
\SetRowColor{LightBackground}
{\bf{UFunc Sinus}} & np.sin(x) & \seqsplit{self-explanatory} \tn 
% Row Count 10 (+ 2)
% Row 14
\SetRowColor{white}
{\bf{UFunc Cosinus}} & np.cos(x) & \seqsplit{self-explanatory} \tn 
% Row Count 12 (+ 2)
% Row 15
\SetRowColor{LightBackground}
{\bf{UFunc Tangent}} & np.tan(x) & \seqsplit{self-explanatory} \tn 
% Row Count 14 (+ 2)
% Row 16
\SetRowColor{white}
{\bf{UFunc Arcsinus (inverse)}} & \seqsplit{np.arcsin(x)} & \seqsplit{self-explanatory} \tn 
% Row Count 17 (+ 3)
% Row 17
\SetRowColor{LightBackground}
{\bf{UFunc Arccosinus (inverse)}} & \seqsplit{np.arccos(x)} & \seqsplit{self-explanatory} \tn 
% Row Count 20 (+ 3)
% Row 18
\SetRowColor{white}
{\bf{UFunc Arctangent (inverse)}} & \seqsplit{np.arctan(x)} & \seqsplit{self-explanatory} \tn 
% Row Count 23 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{{\emph{For matrix dot operation, the number of columns in the first matrix (array) must be equal to the number of rows in the second matrix (array)}}.}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.19002 cm} x{1.69349 cm} x{1.69349 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Aggregates Types}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{array.ufunc.reduce()}} & This aggregate help apply the universal function between elements and returns (reduces) the result toone value (last value) & x = np.arange(1, 6)\{\{nl\}\}np.add.reduce(x)\{\{nl\}\} result : 15 \tn 
% Row Count 9 (+ 9)
% Row 1
\SetRowColor{white}
{\bf{array.ufunc.accumulate()}} & This aggregate help apply the universal function between elements but returns the result of each element inside a list & x = np.arange(1, 6)\{\{nl\}\}np.add.accumulate(x)\{\{nl\}\} result : array({[} 1,  3,  6, 10, 15{]}) \tn 
% Row Count 18 (+ 9)
% Row 2
\SetRowColor{LightBackground}
{\bf{array.ufunc.outer()}} & This aggregate help apply the ufunc operation to all pairs (a, b) with a in A and b in B. & np.multiply.outer({[}1, 2, 3{]}, {[}4, 5, 6{]})\{\{nl\}\} result : array({[}{[} 4,  5,  6{]},{[} 8, 10, 12{]},{[}12, 15, 18{]}{]}) \tn 
% Row Count 26 (+ 8)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{The aggregate for multiplication is : {\bf{array.multiply.reduce()}} \newline The aggregate for subtraction is : {\bf{array.subtract.reduce()}} \newline The aggregate for division is : {\bf{array.divide.reduce()}} \newline The aggregate for addition {\bf{array.add.reduce()}} is equivalent to {\bf{np.sum(array)}} \newline The aggregate for multiplication {\bf{array.multiply.reduce()}} is equivalent to {\bf{np.prod(array)}}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.05271 cm} x{1.00694 cm} x{2.51735 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Other Aggregate Function}}  \tn
% Row 0
\SetRowColor{LightBackground}
np.sum & \seqsplit{np.nansum} & Compute sum of elements \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
np.prod & \seqsplit{np.nanprod} & Compute product of elements \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
np.mean & \seqsplit{np.nanmean} & Compute mean of elements \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
np.std & \seqsplit{np.nanstd} & Compute standard deviation \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
np.var & \seqsplit{np.nanvar} & Compute variance \tn 
% Row Count 10 (+ 2)
% Row 5
\SetRowColor{white}
np.min & \seqsplit{np.nanmin} & Find minimum value \tn 
% Row Count 12 (+ 2)
% Row 6
\SetRowColor{LightBackground}
np.max & \seqsplit{np.nanmax} & Find maximum value \tn 
% Row Count 14 (+ 2)
% Row 7
\SetRowColor{white}
\seqsplit{np.argmin} & \seqsplit{np.nanargmin} & Find index of minimum value \tn 
% Row Count 16 (+ 2)
% Row 8
\SetRowColor{LightBackground}
\seqsplit{np.argmax} & \seqsplit{np.nanargmax} & Find index of maximum value \tn 
% Row Count 18 (+ 2)
% Row 9
\SetRowColor{white}
\seqsplit{np.median} & \seqsplit{np.nanmedian} & Compute median of elements \tn 
% Row Count 20 (+ 2)
% Row 10
\SetRowColor{LightBackground}
\seqsplit{np.percentile} & \seqsplit{np.nanpercentile} & Compute rank-based statistics of elements \tn 
% Row Count 22 (+ 2)
% Row 11
\SetRowColor{white}
\seqsplit{np.any(condition)} & N/A & Evaluate whether any elements are true \tn 
% Row Count 24 (+ 2)
% Row 12
\SetRowColor{LightBackground}
\seqsplit{np.all(condition)} & N/A & Evaluate whether all elements are true \tn 
% Row Count 26 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Python Broadcasting}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{{\bf{Broadcasting}} allows you to perform operations on arrays with different shapes in a way that makes sense, without the need to explicitly reshape or replicate the arrays \newline % Row Count 4 (+ 4)
{\bf{Rules of Broadcasting :}}  \newline % Row Count 5 (+ 1)
Not any operation is permissible when both of arrays have different shapes where :  \newline % Row Count 7 (+ 2)
{\bf{Rule 01 - Padded Dimensions : }} \newline % Row Count 8 (+ 1)
when two have different dimensions we can always add a padding dimension to the left , meaning pushing the first one to the right (5,) =\textgreater{} (1,5) ( adding new axis )  \newline % Row Count 12 (+ 4)
{\bf{Rule 02 - Stretching Dimensions : }} \newline % Row Count 13 (+ 1)
if any of the aligned dimensions is 1 , then we can stretch that dimension to match the other one  \newline % Row Count 15 (+ 2)
A.shape = (2,3) B.shape = (1,3) =\textgreater{} we can stretch B to make it (2,3) \newline % Row Count 17 (+ 2)
{\bf{Example :}} \newline % Row Count 18 (+ 1)
A.shape = (3, 1) \newline % Row Count 19 (+ 1)
B.shape = (3,)  \newline % Row Count 20 (+ 1)
We can padd B =\textgreater{} B.shape = (1,3) \newline % Row Count 21 (+ 1)
This means we can strech both A and B (Both have 1 as aligned dimension) where :  \newline % Row Count 23 (+ 2)
A.shape = (3, 1) =\textgreater{} (3,3) \newline % Row Count 24 (+ 1)
B.shape = (1,3) =\textgreater{} (3,3)% Row Count 25 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{{\bf{if any of these rules doesn't apply then broadcasting is not possible}}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.55618 cm} x{1.51041 cm} x{1.51041 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Numpy Fancy Indexing}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Select Multiple Elements Using Fancy Indexing}} & \seqsplit{select\_elements} = array{[}list\_of\_indexes{]} & \seqsplit{select\_elements} = array1{[}{[}1, 2, 5, 7{]}{]} \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
{\bf{Fancy Indexing for Sorting NumPy Array}} & \seqsplit{sorted\_array} = array{[}np.argsort(array){]} & np.argsort retruns indexes of array sorted (to make it reverse we just write np.argsort(- array)) \tn 
% Row Count 12 (+ 8)
% Row 2
\SetRowColor{LightBackground}
{\bf{Fancy Indexing to Assign New Values to Specific Elements}} & array{[}list\_of\_indices{]} = new\_values & array1{[}{[}1, 3, 6{]}{]} = {[}10, 20, 30{]} \tn 
% Row Count 17 (+ 5)
% Row 3
\SetRowColor{white}
{\bf{Fancy Indexing on N-d Arrays}} & new\_array = array1{[}list\_of\_row\_indices, list\_of\_col\_indices{]} & \seqsplit{selected\_rows} = array1{[}{[}0,2{]}, :{]} \tn 
% Row Count 22 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{{\bf{In fancy indexing we can either put a list of indices or numpy array of indices}}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.46464 cm} x{1.64772 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Numpy Sorting}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Items sort 1}} & \seqsplit{np.sort(array)} & by default it sorts the values in ascending order \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
{\bf{Items sort 2}} & \seqsplit{array.sort()} & this one changes the content of the original array \tn 
% Row Count 8 (+ 4)
% Row 2
\SetRowColor{LightBackground}
{\bf{Index Sorting}} & \seqsplit{np.argsort(array)} & this returns the order of the indexes sorted ascendingly \tn 
% Row Count 12 (+ 4)
% Row 3
\SetRowColor{white}
{\bf{Item Sorting using Index sorting}} & array{[}np.argsort(array){]} & this returns the items sorted ascendingly \tn 
% Row Count 15 (+ 3)
% Row 4
\SetRowColor{LightBackground}
{\bf{Matrix Sorting}} & \seqsplit{np.sort(matrix},axis=0/1) & this sorts either each matrix columns (axis=0) or each matrix row (axis=1) \tn 
% Row Count 21 (+ 6)
% Row 5
\SetRowColor{white}
{\bf{Partitioning (Partial Sorting)}} & \seqsplit{np.partition(array}, n) & this takes the smallest n numbers to the left in no particular order (3 numbers if n = 3) \tn 
% Row Count 28 (+ 7)
% Row 6
\SetRowColor{LightBackground}
{\bf{Matrix Partitioning}} & \seqsplit{np.partition(array}, n, axis=0/1) & this takes the smallest n numbers (of each row or column) to the left in no particular order \tn 
% Row Count 35 (+ 7)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.46464 cm} x{1.64772 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Numpy Sorting (cont)}}  \tn
% Row 7
\SetRowColor{LightBackground}
{\bf{Index Partitioning}} & \seqsplit{np.argpartition(array}, n, axis=0/1) & this is like argsort() but for matrixes \tn 
% Row Count 3 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.55618 cm} x{1.55618 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Array as a Data Structure}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{Empty Structured Arrays}} & \seqsplit{np.zeros(struct\_size}, dtype=\{'names':(col1,col2,col3), \seqsplit{'formats':(form1}, form1, form1)\}) & data = np.zeros(4, dtype=\{'names':('name ', 'age', 'weight'), \seqsplit{'formats':('U10'}, 'i4', 'f8')\}) \{\{nl\}\} \#output : \{\{nl\}\} {[}('', 0, 0.) ('', 0, 0.) ('', 0, 0.) ('', 0, 0.){]} \tn 
% Row Count 13 (+ 13)
% Row 1
\SetRowColor{white}
{\bf{Adding Items to Structured Arrays}} & \# List should be same size as the array structure\{\{nl\}\}struc\_array{[}colname{]} = list & data{[}'name'{]} = name4\{\{nl\}\}data{[}'age'{]} = age4\{\{nl\}\}data{[}'weight'{]} = weight4\{\{nl\}\}\#output:\{\{nl\}\}{[}('Alice', 25, 55. ) ('Bob', 45, 85.5) ('Cathy', 37, 68. ) ('Doug', 19, 61.5){]} \tn 
% Row Count 27 (+ 14)
% Row 2
\SetRowColor{LightBackground}
{\bf{Accessing array strucure columns}} & struct\_array{[}colname{]} & data{[}'name'{]} \tn 
% Row Count 30 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{x{1.46464 cm} x{1.55618 cm} x{1.55618 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{Array as a Data Structure (cont)}}  \tn
% Row 3
\SetRowColor{LightBackground}
{\bf{Accessing array strucure rows}} & struct\_array{[}index{]} & \# Accessing last row \{\{nl\}\} data{[}-1{]} \tn 
% Row Count 3 (+ 3)
% Row 4
\SetRowColor{white}
{\bf{Sorting array strucure}} & \seqsplit{np.sort(struct\_array}, order={[}coumns{]}) & np.sort(data, order={[}'age', 'name'{]}) \tn 
% Row Count 6 (+ 3)
% Row 5
\SetRowColor{LightBackground}
{\bf{Partitioning Structured Arrays}} & \seqsplit{np.partition(struct\_array}, n, order={[}columns{]}) & \# getting the smallest 2 weights to the left \{\{nl\}\}np.partition(data, 2, order={[}'weight'{]})\{\{nl\}\}array({[}('Alice', 25, 55. ), ('Doug', 19, 61.5), ('Cathy', 37, 68. ), ('Bob', 45, 85.5){]} \tn 
% Row Count 21 (+ 15)
% Row 6
\SetRowColor{white}
{\bf{Defining a new data type}} & np.dtype({[}tuple(col\_name,type){]}) & np.dtype({[}('name', 'U10'), ('age', 'i4'), ('weight', 'f8'){]}) \tn 
% Row Count 26 (+ 5)
% Row 7
\SetRowColor{LightBackground}
{\bf{Appending new row}} & \seqsplit{np.append(struct\_array}, numpy\_array{]}, dtype=dt)) & \seqsplit{np.append(data}, np.array({[}('John',64,89){]}, dtype=dt))\{\{nl\}\}{[}('Alice', 25, 55. ) ('Bob', 45, 85.5) ('Cathy', 37, 68. ) ('Doug', 19, 61.5) ('John', 64, 89. ){]} \tn 
% Row Count 38 (+ 12)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{The Format For Empty Structured Arrays are as follows :  \newline - {\bf{Integer}} : np.int32 or 'i4' \newline - {\bf{Float}} : np.float32 or 'f8' \newline - {\bf{String}} : np.str\_ or 'U10'}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}