matplotlib

import matplotlib.pyplot as plt

Basic functions

plt.figure(figsize=(width_inch,height_inch))

Bar chart

plt.bar(x=df['col1'], height=df['col2'],label="col2 count")

plt.plot()

plt.xlabel('col1')

plt.ylabel('col2')

plt.title('chart title')

plt.legend()

plt.show()

Rotate x Lables

plt.xticks(rotation=45,horizontalalignment='right')

Histogram

plt.hist([df['col1'],df['col2']], bins=range(1,101,10))

plt.xticks(range(10,101,10))

plt.yticks(range(10,101,10))

plt.xlabel(['col1','col2'])

plt.ylabel('coly')

plt.title('chart title')

plt.show()

df['col'].hist()

Scatter Plot

plt.scatter(x=df['col1'],y=df['col2']);

Q-Q Plot

import statsmodels.api as sm

import matplotlib.pyplot as plt

g = sm.qqplot(residuals,line='s')

plt.show()

Add Vertical Lines

plt.axvline()

Add Horizontal Lines

plt.axhline()

Subplot

fig, axes = plt.subplots(1,2)

sns.histplot(df['col1],ax = axes[0])

axes[0].set_xlabel('xlabel')

axes[0].set_ylabel('ylabel')

axes[0].set_title('title')

sns.histplot(df['col1],ax = axes[1])

axes[1].set_xlabel('xlabel')

axes[1].set_ylabel('ylabel')

axes[1].set_title('title')

plt.show()

Read Image

img = plt.imread(image_filepath)

Show Image

plt.imshow(img)

Turn off axis on sides

plt.axis('off');

Convert 2D image array to 1D image array

img1D = img.reshape(img.shape[0]*img.shape[1],3)

Construct 1D image dataframe

imgdf = pd.DataFrame(img1D,columns=['r','g','b'])