#193 Annotate matplotlib chart

You can easily spot an interesting point on your chart adding an arrow and some text using the annotate function of matplotlib. See more concerning its use here.

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

# Basic chart
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Annotate with text + Arrow
plt.annotate(
# Label and coordinate
'This point is interesting!', xy=(25, 50), xytext=(0, 80),

# Custom arrow
arrowprops=dict(facecolor='black', shrink=0.05)
)

To add a rectangle, you need to use the patches utility of matplotlib.

# libraries
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Data
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })

# Plot
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Add rectangle
ax1.add_patch(
patches.Rectangle(
(20, 25), # (x,y)
50, # width
50, # height
# You can add rotation as well with 'angle'
alpha=0.3, facecolor="red", edgecolor="black", linewidth=3, linestyle='solid'
)
)

A circle can be added through the patches utility as well.

# Libraries
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Data
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })

# Plot
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Annotation
ax1.add_patch(
patches.Circle(
(40, 35),           # (x,y)
30,                    # radius
alpha=0.3, facecolor="green", edgecolor="black", linewidth=1, linestyle='solid'
)
)

To add a segment, the easiest way is to use the plot function

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

# Basic chart
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Annotation
plt.plot([80, 40], [30, 90], color="skyblue", lw=5, linestyle='solid', label="_not in legend")

You can add horizontal and vertical lines to your plots with axhline and axvline. These lines go from one extremity of your plot to the other.

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

# Plot
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Annotation
plt.axvline(40, color='r')
plt.axhline(40, color='green')

You can write math equation on your chart through the text function.

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

# plot
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')

# Annotation
plt.text(40, 00, r'equation: $\sum_{i=0}^\infty x_i$', fontsize=20)

You can add an ellipse using patches

# libraries
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Data
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })

# Plot
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.plot( 'x', 'y', data=df, linestyle='none', marker='o')
ax1.add_patch(
patches.Ellipse(
(40, 35), # (x,y)
30, # width
100, # height
45, # radius
alpha=0.3, facecolor="green", edgecolor="black", linewidth=1, linestyle='solid'
)
)