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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
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% Document Info
\author{CodingJinxx}
\pdfinfo{
  /Title (codingjinxx-pandas-faq.pdf)
  /Creator (Cheatography)
  /Author (CodingJinxx)
  /Subject (CodingJinxx Pandas FAQ Cheat Sheet)
}

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% Header and Footer
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\fancyhead{} % Set header to blank
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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{CodingJinxx Pandas FAQ Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{CodingJinxx} via \textcolor{DarkBackground}{\uline{cheatography.com/140865/cs/30144/}}}
\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}CodingJinxx \\
  \uline{cheatography.com/codingjinxx} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Published 9th December, 2021.\\
   Updated 10th December, 2021.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
  \SetRowColor{white}
  \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{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{List Comprehension}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list. \newline % Row Count 3 (+ 3)
Example: \newline % Row Count 4 (+ 1)
Based on a list of fruits, you want a new list, containing only the fruits with the letter "a" in the name. \newline % Row Count 7 (+ 3)
Without list comprehension you will have to write a for statement with a conditional test inside: \newline % Row Count 9 (+ 2)
`fruits = {[}"apple", "banana", "cherry", "kiwi", "mango"{]}` \newline % Row Count 11 (+ 2)
`newlist = {[}{]}` \newline % Row Count 12 (+ 1)
`for x in fruits:` \newline % Row Count 13 (+ 1)
`  if "a" in x:` \newline % Row Count 14 (+ 1)
`    newlist.append(x)` \newline % Row Count 15 (+ 1)
`print(newlist)` \newline % Row Count 16 (+ 1)
With list comprehension you can do all that with only one line of code: \newline % Row Count 18 (+ 2)
`fruits = {[}"apple", "banana", "cherry", "kiwi", "mango"{]}` \newline % Row Count 20 (+ 2)
`newlist = {[}x for x in fruits if "a" in x{]}` \newline % Row Count 21 (+ 1)
`print(newlist)`% Row Count 22 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Imputation}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{In statistics, imputation is the process of replacing missing data with substituted values.  \newline % Row Count 2 (+ 2)
When substituting for a data point, it is known as "unit imputation";  \newline % Row Count 4 (+ 2)
when substituting for a component of a data point, it is known as "item imputation".  \newline % Row Count 6 (+ 2)
\{\{popup="https://towardsdatascience.com/pandas-tricks-for-imputing-missing-data-63da3d14c0d6"\}\}Pandas Imputation Article\{\{/popup\}\}% Row Count 9 (+ 3)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.4623 cm} x{8.8077 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Aggregate Functions}}  \tn
% Row 0
\SetRowColor{LightBackground}
sum() & Sums each value of an object \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
count() & Returns total Count \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
median() & Returns mathematical median \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
quantile({[}0.25, 0.75{]}) & Quantiles of an object \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
min() & Lowest value in an object \tn 
% Row Count 9 (+ 2)
% Row 5
\SetRowColor{white}
max() & Highest Value in an Object \tn 
% Row Count 11 (+ 2)
% Row 6
\SetRowColor{LightBackground}
mean() & Returns mathematical mean \tn 
% Row Count 13 (+ 2)
% Row 7
\SetRowColor{white}
var() & Returns mathematical variance \tn 
% Row Count 15 (+ 2)
% Row 8
\SetRowColor{LightBackground}
std() & Returns standard deviation \tn 
% Row Count 17 (+ 2)
% Row 9
\SetRowColor{white}
\seqsplit{df.groupby(by="col")} & Groups data by value of specified column (Similar to SQL)) \tn 
% Row Count 20 (+ 3)
% Row 10
\SetRowColor{LightBackground}
pd.merge(adf, bdf, how='left', on'col') & Merges to Datasheets into one based on a common column \tn 
% Row Count 23 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{Aggregate Functions are a way of summarizing or reshaping data}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Shape of a Dataframe}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Return a tuple representing the dimensionality of the DataFrame. \newline % Row Count 2 (+ 2)
`\textgreater{}\textgreater{}\textgreater{} df = pd.DataFrame(\{'col1': {[}1, 2{]}, 'col2': {[}3, 4{]}\})` \newline % Row Count 4 (+ 2)
`\textgreater{}\textgreater{}\textgreater{} df.shape` \newline % Row Count 5 (+ 1)
`(2, 2)`% Row Count 6 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Mean}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Return the mean of the values over the requested axis. \newline % Row Count 2 (+ 2)
\seqsplit{`DataFrame.mean(axis=None}, skipna=None, level=None, numeric\_only=None)`% Row Count 4 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Median}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Sorts all values in dataframe and returns the middle value \newline % Row Count 2 (+ 2)
\seqsplit{`DataFrame.median(axis=None}, skipna=None, level=None, numeric\_only=None)`% Row Count 4 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Creating a Dataframe from Scratch}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{17.67cm}}{\# Import pandas library \newline import pandas as pd \newline    \newline \# initialize list of lists \newline data = {[}{[}'tom', 10{]}, {[}'nick', 15{]}, {[}'juli', 14{]}{]} \newline    \newline \# Create the pandas DataFrame \newline df = pd.DataFrame(data, columns = {[}'Name', 'Age'{]})} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{17.67cm}}{From Scratch means creating the Data by hand}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Categorical Variable}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Is data that is limited to set or range of values \newline % Row Count 1 (+ 1)
They are best visualised using bar plots or balloon plot \newline % Row Count 3 (+ 2)
\{\{link="http://www.sthda.com/english/articles/32-r-graphics-essentials/129-visualizing-multivariate-categorical-data/"\}\}Example Article\{\{/link\}\}% Row Count 6 (+ 3)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Quartiles vs Quantiles}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Quartiles 25th percentiles of Data \newline % Row Count 1 (+ 1)
Where as Quantiles can be custom percentiles% Row Count 2 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Correlation}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{Correlation describes the relationship between data.  \newline % Row Count 2 (+ 2)
Example: \newline % Row Count 3 (+ 1)
If the square footage in an apartment increases, the price of the apartment increases aswell% Row Count 5 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Scatterplot}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{A Scatterplot plots data on an x-y grid% Row Count 1 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{17.67cm}}{\bf\textcolor{white}{Histogram}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{17.67cm}}{A histogram plots data on a axis with the count being represented in height% Row Count 2 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}



\end{document}