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.
