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# Plotting 

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

# Vanilla matplotlib 

data = np.arange(10)
plt.plot(data)
[<matplotlib.lines.Line2D at 0x26ee1afada0>]

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# Subplots

# subplot(rows, cols, index)
# subplots preferred over plt.plot()
fig = plt.figure()
ax1 = fig.add_subplot(2, 2, 1)
ax2 = fig.add_subplot(2, 2, 2)
ax3 = fig.add_subplot(2, 2, 3) # All 3 should be in the same cell

ax3.plot(np.random.standard_normal(50).cumsum(),
  linestyle="dashed")
ax1.hist(np.random.standard_normal(100), bins=20, alpha=0.3)
ax2.scatter(np.arange(30), np.arange(30) + 3 * np.random.standard_normal(30))
<matplotlib.collections.PathCollection at 0x26ee1d750f0>

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plt.subplots(2, 3, sharex=True, sharey=True) # share shares axis
plt.subplots_adjust(right=2, top=2)

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# Styling
# Add ; to ignore text output
# All methods act on the active or most recently created subplot
plt.plot(np.random.standard_normal(30).cumsum(), color="cyan",
 linestyle="dashed", marker="o", label="Hello")
plt.title("HELLO")

plt.xlabel("x")
plt.ylabel("y")
plt.xticks(range(0, 36, 5)) # x spacing & numbers

plt.legend() # enabled by plot labels

plt.text(20, -1, "HAHAH")
plt.annotate("he", (10, 0.0), arrowprops=dict(facecolor="green", headwidth=4, width=2,
 headlength=4),) # annotate a point
Text(10, 0.0, 'he')

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# Shapes
fig, ax = plt.subplots()
rect = plt.Rectangle((0.2, 0.75), 0.4, 0.15, color="white", alpha=0.3)
circ = plt.Circle((0.7, 0.2), 0.15, color="blue", alpha=0.3)
pgon = plt.Polygon([[0.15, 0.15], [0.35, 0.4], [0.2, 0.6]],
 color="green", alpha=0.5)
ax.add_patch(rect)
ax.add_patch(circ)
ax.add_patch(pgon)
<matplotlib.patches.Polygon at 0x26ee1ddff40>

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# Configure matplotlib
plt.rc(...)
# DataFrame plotting
df = pd.DataFrame(np.random.standard_normal((10, 4)).cumsum(0),
 columns=["A", "B", "C", "D"],
  index=np.arange(0, 100, 10))
df.plot.kde()
<Axes: ylabel='Density'>

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# Barplot
df = pd.DataFrame(np.random.uniform(size=(6, 4)),
 index=["one", "two", "three", "four", "five", "six"],
  columns=pd.Index(["A", "B", "C", "D"], name="Genus"))
df.plot.bar()
<Axes: >

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df.plot.bar(stacked=True)
<Axes: >

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# Seaborn 

sns.barplot(data=df, y="A", orient="h")
c:\Users\ragas\anaconda3\lib\site-packages\seaborn\_oldcore.py:1592: UserWarning: Horizontal orientation ignored with only `y` specified.
  warnings.warn(single_var_warning.format("Horizontal", "y"))





<Axes: ylabel='A'>

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# Histogram
comp1 = np.random.standard_normal(200)
comp2 = 10 + 2 * np.random.standard_normal(200)
values = pd.Series(np.concatenate([comp1, comp2]))
sns.histplot(values, bins=100)
<Axes: ylabel='Count'>

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# Scatterplots
sns.regplot(data=df, x="A", y="B")
<Axes: xlabel='A', ylabel='B'>

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sns.pairplot(data=df)
<seaborn.axisgrid.PairGrid at 0x26ee51042e0>

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