\documentclass[10pt,a4paper]{article}

% Packages
\usepackage{fancyhdr}           % For header and footer
\usepackage{multicol}           % Allows multicols in tables
\usepackage{tabularx}           % Intelligent column widths
\usepackage{tabulary}           % Used in header and footer
\usepackage{hhline}             % Border under tables
\usepackage{graphicx}           % For images
\usepackage{xcolor}             % For hex colours
%\usepackage[utf8x]{inputenc}    % For unicode character support
\usepackage[T1]{fontenc}        % Without this we get weird character replacements
\usepackage{colortbl}           % For coloured tables
\usepackage{setspace}           % For line height
\usepackage{lastpage}           % Needed for total page number
\usepackage{seqsplit}           % Splits long words.
%\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
\usepackage{wasysym}            % Symbols
%\usepackage[english,german,french,spanish,italian]{babel}              % Languages

% Document Info
\author{solider245}
\pdfinfo{
  /Title (pandas.pdf)
  /Creator (Cheatography)
  /Author (solider245)
  /Subject (pandas Cheat Sheet)
}

% Lengths and widths
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\renewcommand{\seqinsert}{\ifmmode\allowbreak\else\-\fi} % Hyphens in seqsplit
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% Commands
\newcommand{\SetRowColor}[1]{\noalign{\gdef\RowColorName{#1}}\rowcolor{\RowColorName}} % Shortcut for row colour
\newcommand{\mymulticolumn}[3]{\multicolumn{#1}{>{\columncolor{\RowColorName}}#2}{#3}} % For coloured multi-cols
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\newcommand{\tn}{\tabularnewline} % Required as custom column type in use

% Font and Colours
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\definecolor{DarkBackground}{HTML}{1A10A3}
\definecolor{LightBackground}{HTML}{F0F0F9}
\renewcommand{\familydefault}{\sfdefault}
\color{TextColor}

% Header and Footer
\pagestyle{fancy}
\fancyhead{} % Set header to blank
\fancyfoot{} % Set footer to blank
\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 Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{solider245} via \textcolor{DarkBackground}{\uline{cheatography.com/83835/cs/19845/}}}
\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}solider245 \\
  \uline{cheatography.com/solider245} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Published 14th June, 2019.\\
   Updated 14th June, 2019.\\
   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}
\raggedright
\raggedcolumns

% Set font size to small. Switch to any value
% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.

\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{pandas安装}}  \tn
% Row 0
\SetRowColor{LightBackground}
conda install pandas & 获得 pandas \seqsplit{的最佳方式是通过} conda \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
python3 -m pip install -{}-upgrade pandas & 通过 PyPI \tn 
% Row Count 5 (+ 2)
% Row 2
\SetRowColor{LightBackground}
pip install \seqsplit{-i https://pypi.tuna.tsinghua.edu.cn/simple gevent} & \seqsplit{使用清华镜像安装} \tn 
% Row Count 9 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{\seqsplit{国内推荐使用清华镜像安装}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{p{0.4977 cm} x{4.4793 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{关键缩写和包导入}}  \tn
% Row 0
\SetRowColor{LightBackground}
df & 任意的Pandas DataFrame对象 \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
s & 任意的Pandas Series对象 \tn 
% Row Count 2 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{缩写}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.23965 cm} x{2.73735 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{引入方法}}  \tn
% Row 0
\SetRowColor{LightBackground}
`import pandas as pd` & \seqsplit{导入pandas并缩写为pd} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{2}{x{5.377cm}}{} \tn 
% Row Count 2 (+ 0)
% Row 2
\SetRowColor{LightBackground}
`import numpy as np` & \seqsplit{导入numpy并缩写为np} \tn 
% Row Count 4 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{常规导入}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.54287 cm} x{3.43413 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{数据选取}}  \tn
% Row 0
\SetRowColor{LightBackground}
df{[}col{]} & \seqsplit{根据列名，并以Series的形式返回列} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
df{[}{[}col1, col2{]}{]} & \seqsplit{以DataFrame形式返回多列} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
s.iloc{[}0{]} & 按位置选取数据 \tn 
% Row Count 5 (+ 1)
% Row 3
\SetRowColor{white}
s.loc{[}'index\_one'{]} & 按索引选取数据 \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
df.iloc{[}0,:{]} & 返回第一行 \tn 
% Row Count 8 (+ 1)
% Row 5
\SetRowColor{white}
df.iloc{[}0,0{]} & \seqsplit{返回第一列的第一个元素} \tn 
% Row Count 10 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{数据清理}}  \tn
% Row 0
\SetRowColor{LightBackground}
df.columns = {[}'a','b','c'{]} & 重命名列名 \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
pd.isnull() & \seqsplit{检查DataFrame对象中的空值，并返回一个Boolean数组} \tn 
% Row Count 6 (+ 4)
% Row 2
\SetRowColor{LightBackground}
pd.notnull() & \seqsplit{检查DataFrame对象中的非空值，并返回一个Boolean数组} \tn 
% Row Count 10 (+ 4)
% Row 3
\SetRowColor{white}
df.dropna() & \seqsplit{删除所有包含空值的行} \tn 
% Row Count 12 (+ 2)
% Row 4
\SetRowColor{LightBackground}
df.dropna(axis=1) & \seqsplit{删除所有包含空值的列} \tn 
% Row Count 14 (+ 2)
% Row 5
\SetRowColor{white}
df.dropna(axis=1,thresh=n) & \seqsplit{删除所有小于n个非空值的行} \tn 
% Row Count 16 (+ 2)
% Row 6
\SetRowColor{LightBackground}
df.fillna(x) & \seqsplit{用x替换DataFrame对象中所有的空值} \tn 
% Row Count 19 (+ 3)
% Row 7
\SetRowColor{white}
s.astype(float) & \seqsplit{将Series中的数据类型更改为float类型} \tn 
% Row Count 22 (+ 3)
% Row 8
\SetRowColor{LightBackground}
s.replace(1,'one') & \seqsplit{用'one'代替所有等于1的值} \tn 
% Row Count 24 (+ 2)
% Row 9
\SetRowColor{white}
s.replace({[}1,3{]},{[}'one','three'{]}) & \seqsplit{用'one'代替1，用'three'代替3} \tn 
% Row Count 26 (+ 2)
% Row 10
\SetRowColor{LightBackground}
\seqsplit{df.rename(columns=lambda} x: x + 1) & 批量更改列名 \tn 
% Row Count 28 (+ 2)
% Row 11
\SetRowColor{white}
df.rename(columns=\{'old\_name': 'new\_ name'\}) & \seqsplit{选择性更改列名} \tn 
% Row Count 31 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{数据清理 (cont)}}  \tn
% Row 12
\SetRowColor{LightBackground}
\seqsplit{df.set\_index('column\_one')} & 更改索引列 \tn 
% Row Count 2 (+ 2)
% Row 13
\SetRowColor{white}
\seqsplit{df.rename(index=lambda} x: x + 1) & \seqsplit{批量重命名索引} \tn 
% Row Count 4 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.15119 cm} x{1.96811 cm} p{0.4577 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{导入数据}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{pd.read\_csv(filename)} & \seqsplit{从CSV文件导入数据} & 1 \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\seqsplit{pd.read\_table(filename)} & \seqsplit{从限定分隔符的文本文件导入数据} & 2 \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\seqsplit{pd.read\_excel(filename)} & \seqsplit{从Excel文件导入数据} & 3 \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
\seqsplit{pd.read\_sql(query}, \seqsplit{connection\_object)} & \seqsplit{从SQL表/库导入数据} & 4 \tn 
% Row Count 10 (+ 3)
% Row 4
\SetRowColor{LightBackground}
\seqsplit{pd.read\_json(json\_string)} & \seqsplit{从JSON格式的字符串导入数据} & 5 \tn 
% Row Count 13 (+ 3)
% Row 5
\SetRowColor{white}
pd.read\_html(url) & \seqsplit{解析URL、字符串或者HTML文件，抽取其中的tables表格} & 6 \tn 
% Row Count 17 (+ 4)
% Row 6
\SetRowColor{LightBackground}
\seqsplit{pd.read\_clipboard()} & \seqsplit{从你的粘贴板获取内容，并传给read\_table()} & 7 \tn 
% Row Count 21 (+ 4)
% Row 7
\SetRowColor{white}
\seqsplit{pd.DataFrame(dict)} & \seqsplit{从字典对象导入数据，Key是列名，Value是数据} & 8 \tn 
% Row Count 25 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{\seqsplit{网上爬取表格一般使用方法6和方法2}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{p{0.4577 cm} x{1.87657 cm} x{2.24273 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{3}{x{5.377cm}}{\bf\textcolor{white}{导出数据}}  \tn
% Row 0
\SetRowColor{LightBackground}
1 & \seqsplit{df.to\_csv(filename)} & \seqsplit{导出数据到CSV文件} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
2 & \seqsplit{df.to\_excel(filename)} & \seqsplit{导出数据到Excel文件} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
3 & \seqsplit{df.to\_sql(table\_name}, \seqsplit{connection\_object)} & \seqsplit{导出数据到SQL表} \tn 
% Row Count 7 (+ 3)
% Row 3
\SetRowColor{white}
4 & \seqsplit{df.to\_json(filename)} & \seqsplit{以Json格式导出数据到文本文件} \tn 
% Row Count 10 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\SetRowColor{LightBackground}
\mymulticolumn{3}{x{5.377cm}}{\seqsplit{一般文件名需要加`''`不知道为什么这里没加}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}---}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{\seqsplit{数据处理：Filter、Sort和GroupBy}}}  \tn
% Row 0
\SetRowColor{LightBackground}
df{[}df{[}col{]} \textgreater{} 0.5{]} & \seqsplit{选择col列的值大于0}.5的行 \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\seqsplit{df.sort\_values(col1)} & \seqsplit{按照列col1排序数据，默认升序排列} \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\seqsplit{df.sort\_values(col2}, ascending=False) & \seqsplit{按照列col1降序排列数据} \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
df.sort\_values({[}col1,col2{]}, ascending={[}True,False{]}) & \seqsplit{先按列col1升序排列，后按col2降序排列数据} \tn 
% Row Count 10 (+ 3)
% Row 4
\SetRowColor{LightBackground}
df.groupby(col) & \seqsplit{返回一个按列col进行分组的Groupby对象} \tn 
% Row Count 13 (+ 3)
% Row 5
\SetRowColor{white}
df.groupby({[}col1,col2{]}) & \seqsplit{返回一个按多列进行分组的Groupby对象} \tn 
% Row Count 16 (+ 3)
% Row 6
\SetRowColor{LightBackground}
df.groupby(col1){[}col2{]} & \seqsplit{返回按列col1进行分组后，列col2的均值} \tn 
% Row Count 19 (+ 3)
% Row 7
\SetRowColor{white}
\seqsplit{df.pivot\_table(index=col1}, values={[}col2,col3{]}, aggfunc=max) & \seqsplit{创建一个按列col1进行分组，并计算col2和col3的最大值的数据透视表} \tn 
% Row Count 24 (+ 5)
% Row 8
\SetRowColor{LightBackground}
\seqsplit{df.groupby(col1).agg(np.mean)} & \seqsplit{返回按列col1分组的所有列的均值} \tn 
% Row Count 27 (+ 3)
% Row 9
\SetRowColor{white}
data.apply(np.mean) & \seqsplit{对DataFrame中的每一列应用函数np}.mean \tn 
% Row Count 30 (+ 3)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{\seqsplit{数据处理：Filter、Sort和GroupBy} (cont)}}  \tn
% Row 10
\SetRowColor{LightBackground}
data.apply(np.max,axis=1) & \seqsplit{对DataFrame中的每一行应用函数np}.max \tn 
% Row Count 3 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.4885 cm} x{2.4885 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{创建测试对象}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{pd.DataFrame(np.random.rand(20},5)) & \seqsplit{创建20行5列的随机数组成的DataFrame对象} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
pd.Series(my\_list) & \seqsplit{从可迭代对象my\_list创建一个Series对象} \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
df.index = \seqsplit{pd.date\_range('1900/1/30'}, periods=df.shape{[}0{]}) & \seqsplit{增加一个日期索引} \tn 
% Row Count 9 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.18988 cm} x{2.78712 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{查看、检查数据}}  \tn
% Row 0
\SetRowColor{LightBackground}
df.head(n) & \seqsplit{查看DataFrame对象的前n行} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
df.tail(n) & \seqsplit{查看DataFrame对象的最后n行} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
df.shape() & 查看行数和列数 \tn 
% Row Count 5 (+ 1)
% Row 3
\SetRowColor{white}
http://df.info() & \seqsplit{查看索引、数据类型和内存信息} \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
df.describe() & \seqsplit{查看数值型列的汇总统计} \tn 
% Row Count 9 (+ 2)
% Row 5
\SetRowColor{white}
\seqsplit{s.value\_counts(dropna=False)} & \seqsplit{查看Series对象的唯一值和计数} \tn 
% Row Count 11 (+ 2)
% Row 6
\SetRowColor{LightBackground}
\seqsplit{df.apply(pd.Series.value\_counts)} & \seqsplit{查看DataFrame对象中每一列的唯一值和计数} \tn 
% Row Count 14 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{2.23965 cm} x{2.73735 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{数据合并}}  \tn
% Row 0
\SetRowColor{LightBackground}
df1.append(df2) & \seqsplit{将df2中的行添加到df1的尾部} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
df.concat({[}df1, df2{]},axis=1) & \seqsplit{将df2中的列添加到df1的尾部} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
df1.join(df2,on=col1,how='inner') & \seqsplit{对df1的列和df2的列执行SQL形式的join} \tn 
% Row Count 7 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.24425 cm} x{3.73275 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{数据统计}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{df.describe()} & \seqsplit{查看数据值列的汇总统计} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
df.mean() & 返回所有列的均值 \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
df.corr() & \seqsplit{返回列与列之间的相关系数} \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
\seqsplit{df.count()} & \seqsplit{返回每一列中的非空值的个数} \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
df.max() & \seqsplit{返回每一列的最大值} \tn 
% Row Count 8 (+ 1)
% Row 5
\SetRowColor{white}
df.min() & \seqsplit{返回每一列的最小值} \tn 
% Row Count 9 (+ 1)
% Row 6
\SetRowColor{LightBackground}
\seqsplit{df.median()} & \seqsplit{返回每一列的中位数} \tn 
% Row Count 11 (+ 2)
% Row 7
\SetRowColor{white}
df.std() & \seqsplit{返回每一列的标准差} \tn 
% Row Count 12 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}


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

\end{document}