I make a loop over two cases and for each case I try to make a plot.
for col_name in ['col2','col3']:
x_min = min(df['col1'].min(), df[col_name].min())
x_max = max(df['col1'].max(), df[col_name].max())
plt.xlim([x_min,x_max])
plt.ylim([x_min,x_max])
plt.axes().set_aspect('equal')
plt.scatter(df['col1'], df[col_name])
As a result I get one plot in my IPython notebook. Does anyone know how to overcome this problem?
You need to call figure() more than once.
for col_name in ['col2','col3']:
plt = figure() #This gives you a new figure to plot in
x_min = min(df['col1'].min(), df[col_name].min())
x_max = max(df['col1'].max(), df[col_name].max())
plt.xlim([x_min,x_max])
plt.ylim([x_min,x_max])
plt.axes().set_aspect('equal')
plt.scatter(df['col1'], df[col_name])
I would just use two figures if I want them on different windows.
Something like this ought to work.
>>> for i in range(3):
xAxis = [randint(1, 5) for _ in range(10)]
plt.figure(1)
plt.plot(xAxis)
plt.show()
xAxis2 = [randint(1, 5) for _ in range(10)]
plt.figure(2)
plt.plot(xAxis2)
plt.show()
It gave me six consecutive figures.
Since, you need a new figure for every iteration, do.
for index, col_name in ['col2','col3']:
plt.figure(index)
# Do the plotting.
