I am creating a Python plot from a dataframe with 3 y-axes. For each y-axis, there are multiple y-values I want to plot. All data sets for the y-axes are plotted against a shared Date x-axis.
The code looks as follows:
df = pd.read_excel (r'test.xlsx', sheet_name='test', engine='openpyxl')
fig, ax = plt.subplots()
ax3 = ax.twinx()
rspine = ax3.spines['right']
rspine.set_position(('axes', 1.15))
ax3.set_frame_on(True)
ax3.patch.set_visible(False)
fig.subplots_adjust(right=0.7)
ax.plot(df['Date'], df['Gas1'], label="Gas1", color='g')
ax.plot(df['Date'], df['Gas2'], label="Gas2", color='b')
ax.plot(df['Date'], df['Gas3'], label="Gas3", marker="o", markersize=2, color='r')
ax.set_xlabel("Date")
ax.set_ylabel("Gas Rate")
ax2 = ax.twinx()
ax2.plot(df['Date'], df['Water1'], label="Water1", color='k')
ax2.plot(df['Date'], df['Water2'], label="Water2", color='y')
ax2.set_ylabel("Water")
ax3.plot(df['Date'], df['Pressure1'], label="Pressure1")
ax3.plot(df['Date'], df['Pressure2'], label="Pressure2")
ax3.set_ylabel("Pressure")
ax.legend()
ax2.legend()
ax3.legend()
plt.show()
The problem I am having is that I want the legends to be outside of the plot, preferably on the right-hand side after the 2nd y-axis. Is this possible? Right now the legends are just overlayed on the plot and not fully visible. I have tried using bbox_to_anchor and loc functions but had no luck. Thank you!
ax.get_legend_handles_labels() collects all the legend handles and their labels. Combining those for each of the axes, a new legend can be created.
bbox_to_anchor= sets an anchor point for the legend, using axes coordinates. loc= needs to be set, to tell which point of the legend's box will get fixed by the anchor.
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
df = pd.DataFrame({'Date': pd.date_range('20210401', periods=30, freq='D'),
'Gas1': np.random.randn(30).cumsum(),
'Gas2': np.random.randn(30).cumsum(),
'Gas3': np.random.randn(30).cumsum(),
'Water1': np.random.randn(30).cumsum(),
'Water2': np.random.randn(30).cumsum(),
'Pressure1': np.random.randn(30).cumsum(),
'Pressure2': np.random.randn(30).cumsum()})
fig, ax = plt.subplots()
ax3 = ax.twinx()
rspine = ax3.spines['right']
rspine.set_position(('axes', 1.15))
ax3.set_frame_on(True)
ax3.patch.set_visible(False)
fig.subplots_adjust(right=0.7)
ax.plot(df['Date'], df['Gas1'], label="Gas1", color='g')
ax.plot(df['Date'], df['Gas2'], label="Gas2", color='b')
ax.plot(df['Date'], df['Gas3'], label="Gas3", marker="o", markersize=2, color='r')
ax.set_ylabel("Gas Rate")
plt.setp(ax.get_xticklabels(), rotation=45, ha='right')
ax2 = ax.twinx()
ax2.plot(df['Date'], df['Water1'], label="Water1", color='k')
ax2.plot(df['Date'], df['Water2'], label="Water2", color='y')
ax2.set_ylabel("Water")
ax3.plot(df['Date'], df['Pressure1'], label="Pressure1")
ax3.plot(df['Date'], df['Pressure2'], label="Pressure2")
ax3.set_ylabel("Pressure")
handles1, labels1 = ax.get_legend_handles_labels()
handles2, labels2 = ax2.get_legend_handles_labels()
handles3, labels3 = ax3.get_legend_handles_labels()
ax.legend(handles=handles1 + handles2 + handles3,
labels=labels1 + labels2 + labels3,
bbox_to_anchor=(1.28, 1.02), loc='upper left')
plt.tight_layout()
plt.show()
Related
I am using secondary y-axis and cmap color but when I plot together the color bar cross to my plot
here is my code
fig,ax1=plt.subplots()
ax1 = df_Combine.plot.scatter('Parameter2', 'NPV (MM €)', marker='s', s=500, ylim=(-10,60), c='Lifetime1 (a)', colormap='jet_r', vmin=0, vmax=25, ax=ax1)
graph.axhline(0, color='k')
plt.xticks(rotation=90)
ax2 = ax1.twinx()
ax2.plot(df_Combine_min_select1["CumEnergy1 (kWH)"])
plt.show()
and here is my plotting
anyone can help how to solve this issue?
Thank you
When you let pandas automatically create a colorbar, you don't have positioning options. Therefore, you can create the colorbar in a separate step and provide the pad= parameter to set a wider gap. Default, pad is 0.05, meaning 5% of the width of the subplot.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
df_Combine = pd.DataFrame({'Parameter2': np.random.rand(10) * 10,
'NPV (MM €)': np.random.rand(10),
'Lifetime1 (a)': np.random.rand(10) * 25,
})
ax1 = df_Combine.plot.scatter('Parameter2', 'NPV (MM €)', marker='s', s=500, ylim=(-10, 60), c='Lifetime1 (a)',
colormap='jet_r', vmin=0, vmax=25, ax=ax1, colorbar=False)
plt.colorbar(ax1.collections[0], ax=ax1, pad=0.1)
ax2 = ax1.twinx()
ax2.plot(np.random.rand(10))
plt.show()
I wrote a code that read an excel sheet and plots a scatter figure with the following code:
fig, ax = plt.subplots(figsize=(13, 8))
scatter = ax.scatter(df.Date, df.TopAcc, c="blue", s=df.Param / 10000, alpha=0.2)
plot = ax.plot(dfmax.Date, dfmax.TopAcc, marker="o", c="red")
handles, labels = scatter.legend_elements(num=5, prop="sizes", alpha=0.2, color="blue")
legend = ax.legend(handles, labels, loc="lower right", title="# Parameters", )
plt.grid()
plt.show()
And I got the following figure
I have the following issues: How to prevent the legend balls from overlapping?
You can set columnspacing in the legend object:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
fig, ax = plt.subplots(figsize=(13, 8))
df = pd.DataFrame(np.random.rand(20, 2), columns=['x', 'y'])
df['s'] = 5000 * np.random.rand(20)
scatter = ax.scatter(df.x, df.y, c="blue", s=df.s, alpha=0.2)
handles, labels = scatter.legend_elements(num=5, prop="sizes", alpha=0.2, color="blue")
legend = ax.legend(handles, labels, loc="lower right", title="# Parameters", ncol=6, columnspacing=3, bbox_to_anchor=(1, -0.12), frameon=False)
plt.grid()
plt.show()
I have problems with the rotation of my X-axis, I have tried to do the rotation the output plot without errors, but I do not have the results.
# Import Data
#df = pd.read_csv("https://github.com/selva86/datasets/raw/master/economics.csv")
x = total_test["Dia"].values[:]; y1 = total_test["Confirmados"].values[:]; y2 = total_test["Fallecidos"].values[:]
# Plot Line1 (Left Y Axis)
fig, ax1 = plt.subplots(1,1,figsize=(10,8), dpi= 200)
ax1.plot(x, y1,'g^', color='tab:red')
# Plot Line2 (Right Y Axis)
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
ax2.plot(x, y2,'bs', color='tab:blue')
# Just Decorations!! -------------------
# ax1 (left y axis)
ax1.set_xlabel('Dias', fontsize=10)
ax1.set_ylabel('Personas Confirmadas', color='tab:red', fontsize=20)
ax1.tick_params(axis='y', rotation=0, labelcolor='tab:red' )
# ax2 (right Y axis)
ax2.set_ylabel("Personas Fallecidas", color='tab:blue', fontsize=20)
ax2.tick_params(axis='y', rotation=0, labelcolor='tab:blue')
ax2.set_title("Personas Confirmadas y Fallecidas por Covid-19 Peru", fontsize=15)
#ax2.set_xticks(x)
ax2.set_xticklabels(x[::],fontsize=10,rotation=90)
plt.show()
Any commands for the xaxis need to occur before ax2.
Verify date is in a datetime format and set as the index.
import pandas as pd
import matplotlib.pyplot as plt
# read data
df = pd.read_csv("https://github.com/selva86/datasets/raw/master/economics.csv")
# verify the date column is a datetime format and set as index
df['date'] = pd.to_datetime(df['date'])
df.set_index('date', inplace=True)
#plot
# create figure
fig, ax1 = plt.subplots(1, 1, figsize=(10,8))
# 1st plot
ax1.plot(df['pop'], color='tab:red')
# set xticks rotation before creating ax2
plt.xticks(rotation=90)
# 2nd plot (Right Y Axis)
ax2 = ax1.twinx() # create the 'twin' axis on the right
ax2.plot(df['unemploy'], color='tab:blue')
plt.show()
Plot directly with pandas.DataFrame.plot
# load data
df = pd.read_csv("https://github.com/selva86/datasets/raw/master/economics.csv", parse_dates=True, index_col=[0])
# plot and rotate the tick labels with rot= in the first plot call
ax = df.plot(y='pop', color='tab:red', figsize=(10,8), rot=90)
ax2 = ax.twinx()
df.plot(y='unemploy', color='tab:blue', ax=ax2)
ax2.legend(loc='upper right')
I have this code for a graph, and I do not want the values & ticks on the top and right axes.
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
#Set axis labels
ax.set_xlabel('NEGATIVE')
ax.set_ylabel('HAPPY')
ax2 = ax.secondary_xaxis('top')
ax2.set_xlabel('POSITIVE')
ax2 = ax.secondary_yaxis('right')
ax2.set_ylabel('SAD')
#Remove ticks/values
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_yticks([])
ax.set_xticks([])
ax2.set_yticklabels([])
ax2.set_xticklabels([])
ax2.set_yticks([])
ax2.set_xticks([])
#Show graph
plt.show()
it's showing it like this: image of graph
Use tick_params to manipulate the axis ticks and labels:
import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
#Set axis labels
ax1.set_xlabel('NEGATIVE')
ax1.set_ylabel('HAPPY')
ax2 = ax1.secondary_xaxis('top')
ax2.set_xlabel('POSITIVE')
ax3 = ax1.secondary_yaxis('right')
ax3.set_ylabel('SAD')
#Remove ticks/values
for ax in (ax1, ax2, ax3):
ax.tick_params(left=False, labelleft=False, top=False, labeltop=False,
right=False, labelright=False, bottom=False, labelbottom=False)
#Show graph
plt.show()
A comment asked for how to only turn top and left ticks and labels off. This would be
for ax in (ax1, ax2, ax3):
ax.tick_params(top=False, labeltop=False, right=False, labelright=False)
Interesting why SecondaryAxis doesn't accept tick params, however let's use twinx and twiny:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
#Set axis labels
ax.set_xlabel('NEGATIVE')
ax.set_ylabel('HAPPY')
ax2x = ax.twiny()
ax2.set_yticks([])
ax2x.set_xlabel('POSITIVE')
ax2y = ax.twinx()
ax2y.set_ylabel('SAD')
ax2x.set_xticks([])
ax2y.set_yticks([])
#Show graph
plt.show()
Output:
I wrote the following code below to do the following graph:
fig, ax = plt.subplots(figsize=(8, 6))
ax.patch.set_facecolor('white')
ax.plot(df.index, df.X1.values, 'b',
label='NMA', linewidth=1.5)
ax.set_ylabel('Index')
ax2 = ax.twinx()
ax2.plot(df.index, df.Y.values, 'r--',
label='Rate', linewidth=1.5)
ax2.set_ylabel('Rate')
lines = ax.get_lines() + ax2.get_lines()
lgd = ax.legend(lines, [line.get_label() for line in lines],
loc='lower center', ncol=2, bbox_to_anchor=(0.5, -0.15),
frameon=False)
ax.set_title('Economic Rate and Index',
weight='bold')
for i in range(5):
plt.axvspan(Dates['Peak'][i], Dates['Trough'][i],
facecolor='grey', alpha=0.5)
plt.grid(False)
plt.savefig('C:\\test.pdf',
bbox_extra_artists=(lgd,), bbox_inches='tight')
I am having a hard time to reproduce this figure in a subplot (2X2). The only thing I would change in each of the subplots is the blue line (X1 in df... for X2, X3...). How can I have a 2X2 subplot of the above graph? Of Course I would only keep one legend at the bottom of the subplots. Thanks for the help.
The data is here and the "Dates" to reproduce the gray bars here.
This is how you could create a 2x2 raster with twinx each:
import matplotlib.pyplot as plt
fig, ((ax1a, ax2a), (ax3a, ax4a)) = plt.subplots(2, 2)
ax1b = ax1a.twinx()
ax2b = ax2a.twinx()
ax3b = ax3a.twinx()
ax4b = ax4a.twinx()
ax1a.set_ylabel('ax1a')
ax2a.set_ylabel('ax2a')
ax3a.set_ylabel('ax3a')
ax4a.set_ylabel('ax4a')
ax1b.set_ylabel('ax1b')
ax2b.set_ylabel('ax2b')
ax3b.set_ylabel('ax3b')
ax4b.set_ylabel('ax4b')
plt.tight_layout()
plt.show()
Result: