Matplotlib 在一个散点图中绘制两个数据框

Question

I am able to plot two indivdiual scatter plots for df5 and df8 using this but I can't seem to plot them on the same figure.

# plot
plt.plot( 'Temperature', 'Moment', data=df5, linestyle='none', marker='o', alpha=0.4, markerfacecolor='lightblue',
         markersize='6')
plt.rcParams["font.family"] ="sans-serif" 
plt.rcParams["font.size"] = 10
plt.xlabel('Temperature(K)')
plt.ylabel('DC Moment (emu)')
fig = plt.figure()
fig.set_figheight(15)
fig.set_figwidth(10)

To plot them on same figure I tried the following but it does not work, it gives a straight line, both the df has same number of rows and columns

x1= df5['Temperature']
y1= df5['Moment']
x2= df8['Temperature']
y2= df8['Moment']

plt.scatter(x1, y1, color= 'g')
plt.scatter(x2, y2, color='b')

Answer 1

You may want to use the build-in matplotlib-based plotting of pandas right away. The only important note is that you need to tell matplotlib to which axis it is supposed to draw the points:

from matplotlib import pyplot as plt

# open figure/axis
fig, ax = plt.subplots()

# plot // you need to specify the axis
df5.plot(x='Temperature', y='Moment', kind='scatter', ax=ax, c='g')
df8.plot(x='Temperature', y='Moment', kind='scatter', ax=ax, c='b')

If you insist on using matplotlib all the way, open a figure with an axis and plot to the same axis:

# open figure/axis
fig, ax = plt.subplots()
ax .scatter(x1, y1, color='g')
# use the same axis object to plot the other values
ax .scatter(x2, y2, color='b')