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

Updated: Mar 23, 2021

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.


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