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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
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% Document Info
\author{cgeeeeh}
\pdfinfo{
  /Title (py-plot.pdf)
  /Creator (Cheatography)
  /Author (cgeeeeh)
  /Subject (Py plot 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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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Py plot Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{cgeeeeh} via \textcolor{DarkBackground}{\uline{cheatography.com/191000/cs/39734/}}}
\end{tabulary}
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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}cgeeeeh \\
  \uline{cheatography.com/cgeeeeh} \\
  \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 4th December, 2023.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
\columnbreak
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  \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
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% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.

\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{analytics and visualization sense}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{Descriptive analytics: analyse and derive  insights from past data.} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Predictive analytics: study trends and predict  what will happen in the future.} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{Prescriptive analytics: analyzed the data, predict what  might happen and provides insights into what steps  should be taken based on the available data and what  the impact of these decisions would be} \tn 
% Row Count 9 (+ 5)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{right data: \seqsplit{百分比数据，各部分数字总和得等与100\%}} \tn 
% Row Count 11 (+ 2)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{right chart：使用正确的图表刻画数据，比如饼状图-\textgreater{}柱状图} \tn 
% Row Count 13 (+ 2)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{right \seqsplit{label：如果不使用label就无法展示信息}} \tn 
% Row Count 15 (+ 2)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{right \seqsplit{axis：一个维度能反映的区别不要用两个维度来做}} \tn 
% Row Count 17 (+ 2)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{不要用3D图装逼} \tn 
% Row Count 18 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{一些小设置}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\%matplotlib \seqsplit{inline。内嵌绘图，并且可以省略掉plt}.show()这一步} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{import matplotlib.pyplot as plt} \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{使用既定画图风格：matplotlib}.style.available; plt.style.use("")} \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{自定义喜欢的风格：matplotlib}.rcParams; matplotlib.rcParams{[}"key"{]}=xxx来设置参数} \tn 
% Row Count 7 (+ 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}{画图函数}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{plt.figure(figsize=(8,6))。设置一个canvas画板} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{fig=plt.figure()。创建画布}} \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{plt.annotate("text", xy, xytext, arrowprops)；xy=(x,y)，坐标根据data的值设置，xytext，arrowprops设置箭头，如\{facecolor="black",shrink=0.05\}} \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{df.plot(kind="TypeOfPlot"}, x="x axis name", y = "y axis name", color="color for points/lines", title="title", legend=True/False)} \tn 
% Row Count 10 (+ 3)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{kind="bar"/"scatter"/"hist"/"box"/"density"/"area"/"pie"}} \tn 
% Row Count 12 (+ 2)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{x=x轴的colname，y=y轴的colname}} \tn 
% Row Count 13 (+ 1)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{plt.plot(x\_data,y\_data, label, color, marker, markerfacecolor, linestyle, \seqsplit{linewidth)。x\_data/y\_data可以是list，也可以是pandas} \seqsplit{series；markerfacecolor是marker里面的填充颜色}} \tn 
% Row Count 17 (+ 4)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{plt.xlabel();plt.title()；plt.xlim(},)；plt.ylim(,); plt.grid(True, linewidth, color, linestyle); plt.xticks()刻度线} \tn 
% Row Count 20 (+ 3)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{plt.legend(loc, title, \seqsplit{title\_fontsize)。loc是图例位置，有upper} \seqsplit{left…；title是图例的标题；title\_fontsize是标题大小}} \tn 
% Row Count 23 (+ 3)
% Row 9
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.axhline(y, c, ls,lw)。绘制水平参考线，y=竖坐标，c=color，ls=line style，lw=线宽} \tn 
% Row Count 25 (+ 2)
% Row 10
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{如果不创建subplot，plt}.plot()/bar()/…函数会不停地在一张图里画} \tn 
% Row Count 27 (+ 2)
% Row 11
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.savefig(path, dpi, \seqsplit{facecolor)。facecolor是图表外图片底色，}} \tn 
% Row Count 29 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1D \seqsplit{plotting（就一列data还硬画）}}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df{[}"colname"{]}.plot(kind)} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.plot({[}1000,2000,3000,4000{]})。跟上面不一样，一个是df调用，一个是plt调用} \tn 
% Row Count 3 (+ 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}{Hexagonal \seqsplit{bin（散点太密集时用它）}}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{数据sample：df = \seqsplit{pd.DataFrame(np.random.randn(1000}, 2), columns={[}"a", "b"{]})  df{[}"b"{]} = df{[}"b"{]} + np.arange(1000)} \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{df.plot.hexbin(x="a", y="b", gridsize=25, C, reduce\_C\_function)} \tn 
% Row Count 5 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{gridsize：控制了x轴方向上的六边形大小，默认值100。更大的size意味着更小更多的bins}} \tn 
% Row Count 8 (+ 3)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{每个六边形会计算范围内的散点，因此涉及到【计算什么值】和【怎么计算值】。C：每个（x},y）被用于计算的value；reduce\_C\_function：聚合后计算的方法，有mean, max, sum, std} \tn 
% Row Count 13 (+ 5)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{模型情况，hexbin仅count周围散点的数量}} \tn 
% Row Count 14 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Bar plot}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{有label非时间series-\textgreater{}单列柱图：df.iloc{[}5{]}.plot.bar()} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{dataframe-\textgreater{}多列柱图（垂直）：df.plot.bar(stacked)。stacked=True/False} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{dataframe-\textgreater{}多列柱图（水平）：df2.plot.barh(stacked)} \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{plt.bar(参数跟之前的同理}, width, \seqsplit{align)；width控制桌子的宽度；align控制柱子对其的位置，有edge/center}} \tn 
% Row Count 9 (+ 3)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{在一个figure中连续调用bar函数，需要用x轴坐标+width来控制柱子的位置错开}} \tn 
% Row Count 11 (+ 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}{Pie}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{数据sample：series = pd.Series(3 * np.random.rand(4), index={[}"a", "b", "c", "d"{]}, name="series")} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{series.plot.pie(figsize=(6}, 6),legends, colors, autopct="\%.2f", fontsize)} \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{饼状图适合方形：因此使用figsize或ax}.set\_aspect('equal')} \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{单图：y参数指定一列}} \tn 
% Row Count 7 (+ 1)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{多图：subplots=True} \tn 
% Row Count 8 (+ 1)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{legends：True/False决定要不要；None决定有没有文字；{[}"AA", "BB", "CC", "DD"{]}} \tn 
% Row Count 10 (+ 2)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{colors={[}"r", "g", "b", "c"{]}；autopct控制显示的数值格式} \tn 
% Row Count 12 (+ 2)
% Row 7
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{如果数据的和不足1，他们会被rescale}} \tn 
% Row Count 13 (+ 1)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{plt.pie(data, labels, explode, autopct, \seqsplit{wedgeprops)。这个函数跟pandas的区别是总和不足1时不会自动rescale}} \tn 
% Row Count 16 (+ 3)
% Row 9
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{explode参数长度跟data，label一样，控制每个部分外移的距离；autopct决定label的显示格式"2}.1f"；wedgeprops能让饼图变成环图，如\{width: 0.3\}，width设1即为饼图} \tn 
% Row Count 21 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{2D \seqsplit{plotting（终于正常一点）}}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df.plot(kind,x,y,color)} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.plot({[}1,2,3,4{]}, {[}1000,2000,3000,4000{]}, color, marker, \seqsplit{linestyle)。marker是点的颜色，linestyle是线的风格}} \tn 
% Row Count 4 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{sns.countplot(df,x="Creditability")} \tn 
% Row Count 5 (+ 1)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{sns.catplot(df,x='Creditability',y="Credit Amount",kind="violin")} \tn 
% Row Count 7 (+ 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}{Box}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df.plot.box(column={[}"Col1", "Col2"{]}, color=color, sym="r+", vert=False, positions={[}1, 4, 5, 6, 8{]}, \seqsplit{by="X")。sym参数决定异常点形状，vertical=False让箱线图横过来，positions自定义箱线图距离}} \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{color = \{"boxes": "DarkGreen", "whiskers": "DarkOrange", "medians": "DarkBlue", "caps": "Gray", \}} \tn 
% Row Count 7 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{by={[}"X","Y"{]}是指根据df的"X"这一列group，然后分组绘制箱线图。每一个箱线图是一个group内每个列的箱线图} \tn 
% Row Count 10 (+ 3)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{也可以先分组再画分组箱线图：df\_box}.groupby("g").boxplot()} \tn 
% Row Count 12 (+ 2)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{sns.boxplot(data=df{[}"Credit Amount"{]})} \tn 
% Row Count 13 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Area}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{数据sample：df = \seqsplit{pd.DataFrame(np.random.rand(10}, 4), columns={[}"a", "b", "c", "d"{]})} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{df.plot.area(stacked)} \tn 
% Row Count 3 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{histogram}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df.plot.hist(stacked, bins, alpha, orientation="horizontal", cumulative=True)} \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{alpha是颜色透明度，bins是分桶数量，orientation决定了是横着的还是竖着的直方图，cumulative=True意味着不断累积，最后一个柱子的长度是1}} \tn 
% Row Count 6 (+ 4)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df.hist(figsize=(50,50))也可以画} \tn 
% Row Count 7 (+ 1)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.hist(y\_data, bin\_data, label)} \tn 
% Row Count 8 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Scatter}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{数据sample：df = \seqsplit{pd.DataFrame(np.random.rand(50}, 4), columns={[}"a", "b", "c", "d"{]})  df{[}"species"{]} = pd.Categorical(     {[}"setosa"{]} {\emph{ 20 + {[}"versicolor"{]} }} 20 + {[}"virginica"{]} * 10 )} \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{df.plot.scatter(x="a", y="b", color, label, c)} \tn 
% Row Count 5 (+ 1)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{c="colname"，这个col会被用于cmap，决定每个散点的颜色。如果是类别变量则cmap会是个分段映射}} \tn 
% Row Count 8 (+ 3)
% Row 3
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{s=size。控制每个散点的大小}} \tn 
% Row Count 9 (+ 1)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{画两组散点在同一个图：ax} = df.plot.scatter(x="a", y="b", color="DarkBlue", label="Group 1")  df.plot.scatter(x="c", y="d", color="DarkGreen", label="Group 2", ax=ax);} \tn 
% Row Count 13 (+ 4)
% Row 5
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{plt.scatter(days, y\_views, label, 其他的同理)；} \tn 
% Row Count 15 (+ 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}{3D plotting}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{df.plot.scatter(x,y,s=df{[}"colname"{]})} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{\seqsplit{s=第三维度，如scatter图里是散点的大小}} \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{sns.heatmap(df.corr())} \tn 
% Row Count 4 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}


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

\end{document}