python - Matplotlib/Pandas: How to plot multiple scatterplots within different locations in the same plot? -

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i have 2 pandas dataframes, plot within same plot. these 2 samples, , contrast properties, example:

enter image description here

the x axis has 2 locations, left first dataset, , right second dataset.

in matplotlib, 1 can plot multiple datasets within same plot:

import matplotlib.pyplot plt  x = range(100) y = range(100,200) fig = plt.figure() ax1 = fig.add_subplot(111)  ax1.scatter(x[:4], y[:4], s=10, c='b', marker="s", label='first') ax1.scatter(x[40:],y[40:], s=10, c='r', marker="o", label='second') plt.show()

enter image description here

however,

(1) how separate datasets 2 compartmentalized locations first example?

(2) how accomplish 2 pandas dataframes? merge them , specify 2 locations plotting?

use return_type='axes' data1.boxplot return matplotlib axes object. pass axes second call boxplot using ax=ax. cause both boxplots drawn on same axes.

ax = df1.plot() df2.plot(ax=ax)    a1=a[['a','time']] ax = a1.boxplot(by='time', meanline=true, showmeans=true, showcaps=true,              showbox=true, showfliers=false, return_type='axes') a2 = a[['c','time']] a2.boxplot(by='time', meanline=true, showmeans=true, showcaps=true,         showbox=true, showfliers=false, ax=ax)

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