Bar Plot

• Standard Bar Pot
• Stacked Bar Plot
  • Percentage Stacked Bar Plot
  • Overlapped Bar Plot
  • Grouped Bar Plot
• Accurate Bar Plot
  • Principle of proportion ink
    • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented
  • sorting data
    • In Pandas we can use sort_values(), sort_index()
    • Sort in many ways a find patterns
  • Use appropriate spaces
    • Matplotlib techniques
  • Simplicity
  • ETC

Line Plot

Basic Line plot

• .plot()

• Best for sequence data

• Elements for line plot

  1. color
  2. marker, markersize
  3. linestyle, linewidth

  matplotlib.markers - Matplotlib 3.5.1 documentation

fig, ax= plt.subplots(1,1, figsize=(5,5))     
np.random.seed(97)
x = np.arange(7)
y = np.random.rand(7)

ax.plot(x,y, color = 'tomato', marker='^', 
        linestyle='--')

• Smooth the data to reduce the noise

Accurate line plot

• Changing gaps between data can generate misunderstandings

  • Trends can be misunderstood
  • Plots will seem to have a data that is not there

• Interpolation

  • Moving Average

  google_rolling=google.rolling(window=10).mean()
  

  • Smooth Curve with scipy

  How to Plot a Smooth Curve in Matplotlib? - GeeksforGeeks

• Dual axis

  • .twinx()
  • .secondary_xaxis(), .secondary_yaxis()

  Secondary Axis - Matplotlib 3.5.1 documentation

• ETC

  • MIn/Max
  • Using labels at the end
  • Uncertainty

Scatter Plot

Basic Scatter Plot

• .scatter()
• Elements of scatter plot (2D → nD)
  1. color
  2. marker
  3. size