Plotting Line Graph, Bar Graph, Histogram, Box Graph, and Heat Map in Data Science and ML

In this blog, we will learn how to plot graphs in data science using pandas, sklearn, and matplotlib.

Plotting Line Graph

#plotting line graph

plt.plot(path_of_csv['Column name of csv '])

plt.xlabel('x')

plt.ylabel('y')

label = ['jan', 'feb', 'mar']

plt.xticks(np.arange(0, 50, 5), label)

plt.yticks(np.arange(0, 100, 25))

plt.title('your title here')

plt.show()

or

Without CSV:

field = [1,2,3]

plt.plot(field)

plt.xlabel('x')

plt.ylabel('y')

label = ['jan', 'feb', 'mar']

plt.xticks(np.arange(0, 10, 2), label)

plt.yticks(np.arange(0, 75, 25))

plt.title('your title here')

plt.show()

The plot display like this:

Plotting Box Graph:

#Ploting Box graph

Using CSV:

Data = read_csv("csv_file")

plt.figure(figsize=(10,8))

Data.boxplot('column_name', vert=False)

or #sns.boxplot(x='x', y='y', data=Data)

plt.xlabel('x')

plt.title('your title here')

plt.show()

Plotting Histogram Graph:

#Ploting Histogram graph

Using CSV:

#Ploting histogram

plt.figure(figsize=(20,10))

Data ['columnname'].plot.hist(bins=50,

color='#607c8e')

plt.yticks([0,250,500])

plt.xlabel('x')

plt.title('write title hre')

plt.ylabel('y')

Plotting Heat-map:

#Ploting Heat-map

Using CSV:

Code:

csv_file_data = read_csv("filename")

Data = csv_file_data [ csv_file_data ['Days']

data_table = Data .pivot_table(index=Data['date'].dt.hour,

columns='Data_column1',

values='Data_column2',

aggfunc='sum')

fig, ax = plt.subplots()

ax.set_title('write title here')

heatmap1 = ax.pcolor(data_table )

plt.colorbar(heatmap1)

plt.yticks(np.arange(0, len(data_table .index), 1), data_table .index)

plt.xticks(np.arange(0, len(data_table .columns), 1), data_table .columns)

plt.show()

It look like that:

Thanks for reading this, if you need any help related to the data science graph then please contact here or comments below if suggests anything related to the plot.