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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
\usepackage{amsmath}            % Symbols
\usepackage{MnSymbol}           % Symbols
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% Document Info
\author{Daryabi}
\pdfinfo{
  /Title (pandas-groupby.pdf)
  /Creator (Cheatography)
  /Author (Daryabi)
  /Subject (pandas groupby 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}}
    }
\end{tabulary}
\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{pandas groupby Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Daryabi} via \textcolor{DarkBackground}{\uline{cheatography.com/181709/cs/37835/}}}
\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}Daryabi \\
  \uline{cheatography.com/daryabi} \\
  \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 21st March, 2023.\\
   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{multicols*}{2}

\begin{tabularx}{8.4cm}{x{2 cm} x{6 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Pandas objects}}  \tn
% Row 0
\SetRowColor{LightBackground}
Series & a one-dimensional labeled array that can hold any data type \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
DataFrame & a two-dimensional labeled data structure with columns of potentially different types \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
Index & a sequence of axis labels that can be used to identify rows or columns in a DataFrame \tn 
% Row Count 8 (+ 3)
% Row 3
\SetRowColor{white}
\seqsplit{MultiIndex} & a hierarchical index object that allows for more than one index level in a DataFrame. \tn 
% Row Count 11 (+ 3)
% Row 4
\SetRowColor{LightBackground}
Timestamp & a specific moment in time, represented in Pandas as a datetime object. \tn 
% Row Count 14 (+ 3)
% Row 5
\SetRowColor{white}
Period & a specific interval of time, represented in Pandas as a period object. \tn 
% Row Count 17 (+ 3)
% Row 6
\SetRowColor{LightBackground}
\seqsplit{DatetimeIndex} & an index of datetime objects, used to index Pandas objects like Series and DataFrame. \tn 
% Row Count 20 (+ 3)
% Row 7
\SetRowColor{white}
Timedelta & a duration of time, represented in Pandas as a timedelta object. \tn 
% Row Count 23 (+ 3)
% Row 8
\SetRowColor{LightBackground}
\seqsplit{Categorical} & a data type used to represent categorical variables, \tn 
% Row Count 25 (+ 2)
% Row 9
\SetRowColor{white}
Sparse & a data structure used to represent sparse data efficiently, \tn 
% Row Count 27 (+ 2)
% Row 10
\SetRowColor{LightBackground}
Interval & a data type used to represent intervals \tn 
% Row Count 29 (+ 2)
% Row 11
\SetRowColor{white}
\seqsplit{DatetimeTZ} & a datetime object with a timezone. \tn 
% Row Count 31 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{2.4 cm} x{5.6 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Pandas functions called on pd}}  \tn
% Row 0
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\seqsplit{pd.read\_csv()} & used to read data from a CSV file and create a DataFrame. \tn 
% Row Count 3 (+ 3)
% Row 1
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\seqsplit{pd.DataFrame()} & a constructor function that is used to create a new DataFrame from data in memory. \tn 
% Row Count 6 (+ 3)
% Row 2
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\seqsplit{pd.Series():} & used to create a new Series object. \tn 
% Row Count 8 (+ 2)
% Row 3
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pd.concat() & used to concatenate two or more DataFrames or Series \tn 
% Row Count 10 (+ 2)
% Row 4
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pd.merge(): & used to merge two DataFrames based on a common column. \tn 
% Row Count 12 (+ 2)
% Row 5
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\seqsplit{pd.groupby()} & used to group data in a DataFrame based on one or more columns. \tn 
% Row Count 15 (+ 3)
% Row 6
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\seqsplit{pd.pivot\_table():} & used to create a pivot table from a DataFrame. \tn 
% Row Count 17 (+ 2)
% Row 7
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\seqsplit{pd.to\_datetime():} & used to convert a column of strings to datetime objects. \tn 
% Row Count 19 (+ 2)
% Row 8
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\seqsplit{pd.to\_numeric()} & used to convert a column of strings to numeric objects. \tn 
% Row Count 21 (+ 2)
% Row 9
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pd.cut() & This function is used to bin data into discrete intervals. \tn 
% Row Count 24 (+ 3)
% Row 10
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pd.qcut(): & This function is used to bin data into quantiles. \tn 
% Row Count 26 (+ 2)
% Row 11
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\seqsplit{pd.date\_range()} & used to create a range of dates or DatetimeIndex. \tn 
% Row Count 28 (+ 2)
% Row 12
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\seqsplit{pd.timedelta()} & used to create a timedelta object representing a duration of time. \tn 
% Row Count 31 (+ 3)
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\begin{tabularx}{8.4cm}{x{3.04 cm} x{4.96 cm} }
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\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{String vectorization}}  \tn
% Row 0
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str.replace(): & used to replace a pattern in a string with another pattern \tn 
% Row Count 3 (+ 3)
% Row 1
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str.extract() & used to extract a pattern from a string and return the first match. \tn 
% Row Count 6 (+ 3)
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str.split() & used to split a string into a list of strings based on a delimiter. \tn 
% Row Count 9 (+ 3)
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str.join() & used to concatenate a list of strings with a separator string \tn 
% Row Count 12 (+ 3)
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\seqsplit{str.startswith()} & used to check if a string starts with a particular substring \tn 
% Row Count 15 (+ 3)
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str.endswith() & used to check if a string ends with a particular substring \tn 
% Row Count 18 (+ 3)
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str.lower(), str.upper(): & used to convert the case of a string to lowercase or uppercase, respectively \tn 
% Row Count 22 (+ 4)
% Row 7
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str.strip(): & used to remove leading and trailing whitespace from a string \tn 
% Row Count 25 (+ 3)
% Row 8
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str.contains() & used to check if a pattern exists in a string \tn 
% Row Count 27 (+ 2)
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\begin{tabularx}{8.4cm}{x{3.84 cm} x{4.16 cm} }
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\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Date Vectorization}}  \tn
% Row 0
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pd.to\_datetime(): & used to convert a column of strings or Unix timestamps to a datetime object. \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
dt.date & used to extract the date component of a datetime object or DatetimeIndex. \tn 
% Row Count 8 (+ 4)
% Row 2
\SetRowColor{LightBackground}
dt.time & extract the time component of a datetime object or DatetimeIndex. \tn 
% Row Count 12 (+ 4)
% Row 3
\SetRowColor{white}
dt.hour, dt.minute, dt.second & used to extract the hour, minute, and second components of a datetime object or DatetimeIndex. \tn 
% Row Count 17 (+ 5)
% Row 4
\SetRowColor{LightBackground}
dt.dayofweek: & used to extract the day of the week as an integer, \tn 
% Row Count 20 (+ 3)
% Row 5
\SetRowColor{white}
dt.day\_name() & used to extract the name of the day of the week \tn 
% Row Count 23 (+ 3)
% Row 6
\SetRowColor{LightBackground}
dt.month\_name() & used to extract the name of the month \tn 
% Row Count 25 (+ 2)
% Row 7
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dt.tz\_localize() and dt.tz\_convert(): & used to set or convert the timezone of a datetime object or DatetimeIndex. \tn 
% Row Count 29 (+ 4)
% Row 8
\SetRowColor{LightBackground}
\seqsplit{dt.is\_month\_start} and dt.is\_month\_end & used to check if a datetime object or DatetimeIndex is at the start or end of a month, respectively. \tn 
% Row Count 34 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
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\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{pandas groupby}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{8.4cm}}{Consider it as DataFrame; you can use all DataFrame attributes and functions on the group object.% Row Count 2 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{1.84 cm} x{6.16 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Pandas pivot\_table}}  \tn
% Row 0
\SetRowColor{LightBackground}
data & The DataFrame or Series to be used for the pivot table. \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
values & The column to aggregate. If not specified, all numerical columns will be used. \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
index & The column(s) to use as row labels. \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
columns & The column(s) to use as column labels. \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
aggfunc & The function to use for aggregating the values. Defaults to 'mean'. \tn 
% Row Count 12 (+ 3)
% Row 5
\SetRowColor{white}
margins & Add all row/columns (e.g. 'All') label and compute grand total for that row/column. \tn 
% Row Count 15 (+ 3)
% Row 6
\SetRowColor{LightBackground}
\seqsplit{margins\_name} & The label for the row/column that contains the grand total. Defaults to 'All'. \tn 
% Row Count 18 (+ 3)
% Row 7
\SetRowColor{white}
dropna & Whether or not to exclude rows with missing values. Defaults to True. \tn 
% Row Count 21 (+ 3)
% Row 8
\SetRowColor{LightBackground}
sort & Whether or not to sort the rows by the values of the index. \tn 
% Row Count 23 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{8.4cm}}{\bf\textcolor{white}{Pandas multiIndex}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{8.4cm}}{\# Create a MultiIndex from two separate indexes \newline index1 = pd.Index({[}'A', 'B', 'C'{]}, name='Index1') \newline index2 = pd.Index({[}'X', 'Y', 'Z'{]}, name='Index2') \newline multi\_index = pd.MultiIndex.from\_product({[}index1, index2{]}, names={[}'Index1', 'Index2'{]}) \newline  \newline \# Create a MultiIndex from a list of tuples \newline tuples = {[}('A', 'X'), ('A', 'Y'), ('B', 'X'), ('B', 'Y'){]} \newline multi\_index = \seqsplit{pd.MultiIndex.from\_tuples(tuples}, names={[}'Index1', 'Index2'{]}) \newline  \newline \# Select data from a single level of the index \newline df.loc{[}'A'{]}  \# selects all rows where Index1 = 'A' \newline df.loc{[}('A', 'X'){]}  \# selects a single row where Index1 = 'A' and Index2 = 'X' \newline  \newline \# Select data from multiple levels of the index \newline \# selects rows where Index1 is 'A' or 'B' and Index2 is 'X', and returns the 'Column1' values \newline df.loc{[}({[}'A', 'B'{]}, 'X'), 'Column1'{]}  \newline  \newline \# Stack a DataFrame to move a level of the MultiIndex to the columns \newline df.stack() \newline  \newline \# Unstack a DataFrame to move a level of the columns to the index \newline df.unstack()} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}


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

\end{document}