[Matplotlib-users] matplotlib - extend x-axis labels and scaling problem

[Scott Lasley]

There may be a better way to do this, but you can manually set xlim, xticks and xticklabels to cover the entire data range.  Use ax.legend() and ax2.legend() to show both legends.  Use set_ylim and get_ylim to set both y axes to the same scale.  

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

cl1='red'
cl2='blue'
cl3='grey'

df1 = pd.DataFrame(data=np.random.standard_normal(31),
                   columns=['df1'],
                   index=pd.date_range('2020-01-01', '2020-01-01 00:30', freq='T'))
df2 = pd.DataFrame(data=np.random.standard_normal(61) * 4,
                   columns=['df2'],
                   index=pd.date_range('2020-01-01', '2020-01-01 01', freq='T'))

fig, ax = plt.subplots(1, 1, figsize=(16, 9), dpi=90,
                       tight_layout=True)

df1.plot(ax=ax, color=cl1)
ax.set_xlabel('time', color=cl3, fontsize=20)
ax.tick_params(axis='x', rotation=0, labelcolor=cl3, labelsize=12)
ax.set_ylabel('SEND', color=cl1, fontsize=20)
ax.tick_params(axis='y', rotation=0, labelcolor=cl1)
ax.grid(alpha=.4)
ax.set_title('Title', color=cl3)

ax2 = ax.twinx()
ax2.tick_params(axis='x', rotation=0, labelcolor=cl3, labelsize=12)
df2.plot(ax=ax2, color=cl2)
ax2.set_ylabel('RECV', color=cl2, fontsize=20)
ax2.tick_params(axis='y', labelcolor=cl2)

# pandas sets the label to the column name so set labels here
ax.legend(loc='upper left', labels=['leftfilter'])
ax2.legend(loc='upper right', labels=['rightreceived'])

# set x ticks and tick labels.  Use start, end and freq values 
# valid for your data
tiks = pd.date_range(start=df1.index.min(), 
                     end=df2.index.max(), 
                     freq='5T')
ax.set_xlim(tiks[0], tiks[-1])
ax.set_xticks(tiks);
ax.set_xticklabels(tiks.time)

# set left y limits to the right y limit values that were automatically 
# set by df2.plot().  could also set both ax and ax2 y limits to the same 
# values you choose
ax.set_ylim(ax2.get_ylim());
# ylimits = [0, 20]
# ax.set_ylim(ylimits)
# ax2.set_ylim(ylimits)




> On Mar 25, 2020, at 7:05 AM, Duncan Kerr <duncan.kerr at live.com> wrote:
> 
> 
>> 
>> I have a couple of issues, trying to plot two y axes.  How do I
>> 
>> make grid cover whole area of plot
>> 
>> make xaxis labels go all way to right
>> 
>> make both y axes use same scale
>> 
>> get a legend for both plots onto the graph.
>> 
>> my graph and code are as follows:
>> 
>> <decchfafllgghohe.png>
>> 
>> #!c:/python/python
>> 
>> import 
>> sys
>> 
>> import numpy as 
>> np
>> 
>> import pandas as 
>> pd
>> 
>> import matplotlib as 
>> mpl
>> 
>> import matplotlib.pyplot as 
>> plt
>> 
>> import seaborn as 
>> sns
>> 
>> import 
>> warnings;
>> 
>> warnings.filterwarnings(
>> action='once'
>> )
>> 
>> plt.style.use(
>> 'seaborn-whitegrid'
>> )
>> sns.set_style(
>> "white"
>> )
>> 
>> cl1=
>> 'red'
>> 
>> cl2=
>> 'blue'
>> 
>> cl3=
>> 'grey'
>> 
>> 
>> print("expected title filter1 filter3 file1 file2"
>> )
>> 
>> print("called with "+sys.argv[1]+","+sys.argv[2]+","+sys.argv[3]+","+sys.argv[4
>> ])
>> 
>> # Version
>> 
>> print(mpl.__version__)  
>> # > 3.0.0
>> 
>> print(sns.__version__)  
>> # > 0.9.0
>> 
>> # Import Data
>> 
>> dfr = pd.read_csv(sys.argv[4
>> ])
>> dfs = pd.read_csv(sys.argv[
>> 5
>> ])
>> xyr = dfr.groupby([
>> 'c1']).count()['c2'
>> ]
>> xys = dfs.groupby([
>> 'c1']).count()['c2'
>> ]
>> 
>> fig, ax = plt.subplots(
>> 1, 1, figsize=(16, 9), dpi=90
>> )
>> 
>> 
>> # print data for plots
>> 
>> print(dfr.groupby('c1'
>> ).count())
>> 
>> dfr.groupby([
>> 'c1']).count()['c2'].plot(ax=ax,color=cl1, label='leftfilter'
>> )
>> 
>> 
>> # Decorations
>> 
>> # ax1 (left Y axis)
>> 
>> ax.set_xlabel('time', color=cl3, fontsize=20
>> )
>> ax.tick_params(
>> axis='x', rotation=0, labelcolor=cl3, labelsize=12
>> )
>> ax.set_ylabel(sys.argv[
>> 2], color=cl1, fontsize=20
>> )
>> ax.tick_params(
>> axis='y', rotation=0, labelcolor
>> =cl1)
>> ax.grid(
>> alpha=.4
>> )
>> s = 
>> "%s min %d max %d avg %d std %d" 
>> % (
>> sys.argv[
>> 1], dfr.groupby('c1').count().min()['c2'], dfr.groupby('c1').count().max()['c2'
>> ],
>> dfr.groupby(
>> 'c1').count().mean()['c2'], dfs.groupby('c1').count().std()['c2'
>> ])
>> ax.set_title(s, 
>> color
>> =cl3)
>> 
>> 
>> 
>> # ax2 (right Y axis)
>> 
>> ax2 = ax.twinx()  
>> # instantiate a second axes that shares the same x-axis
>> 
>> ax2.tick_params(axis='x', rotation=0, labelcolor=cl3, labelsize=12
>> )
>> dfs.groupby([
>> 'c1']).count()['c2'].plot(ax=ax2, color
>> =cl2)
>> ax2.set_ylabel(sys.argv[
>> 3], color=cl2, fontsize=20
>> )
>> ax2.tick_params(
>> axis='y', labelcolor
>> =cl2)
>> fig.tight_layout()
>> 
>> # place legend in good spot
>> 
>> #plt.legend(loc=0)
>> 
>> plt.show()
>> 
>> 
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