Visualize Plot and Subplots using Matplotlib and Python - P1
Visualize Plot and Subplots using Matplotlib and Python
Topic to be Covered - Data Visualisation
Link for the Dataset - http://www.randalolson.com/2014/06/14...
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('percent-bachelors-degrees-women-usa.csv')
No 1
plt.plot(df['Year'],df['Agriculture'],color='red')
plt.plot(df['Year'],df['Architecture'],color='blue')
plt.plot(df['Year'],df['Art and Performance'],color='green')
plt.plot(df['Year'],df['Physical Sciences'],color='red')
plt.plot(df['Year'],df['Computer Science'],color='blue')
No 2
'''
1 2 3
1 x 3
1,3,1
1,3,2
1,3,3'''
plt.subplot(1,3,1)
plt.plot(df['Year'],df['Architecture'],color='blue')
plt.title('Architecture')
plt.subplot(1,3,2)
plt.plot(df['Year'],df['Computer Science'],color='green')
plt.title('Computer Science')
plt.subplot(1,3,3)
plt.plot(df['Year'],df['Physical Sciences'],color='yellow')
plt.title('Physical Sciences')
plt.show()
No 3
plt.plot(df['Year'], 100 -df['English'],c='blue',label='Men')
plt.plot(df['Year'], df['English'],c='red',label='Women')
plt.title('English Enrollment Comparion between the gender')
plt.xlabel('Year')
plt.ylabel('Enrollment in percentage')
No 4
'''
1 2 3
4 5 6
7 8 9
10 11 12
13 14 15
16 17
6 x 3'''
fig = plt.figure(figsize=(13,5))
ax1 = fig.add_subplot(6,3,1)
ax2 = fig.add_subplot(6,3,2)
ax3 = fig.add_subplot(6,3,3)
ax4 = fig.add_subplot(6,3,4)
ax5 = fig.add_subplot(6,3,5)
ax6 = fig.add_subplot(6,3,6)
ax7 = fig.add_subplot(6,3,7)
ax8 = fig.add_subplot(6,3,8)
ax9 = fig.add_subplot(6,3,9)
ax10 = fig.add_subplot(6,3,10)
ax11 = fig.add_subplot(6,3,11)
ax12 = fig.add_subplot(6,3,12)
ax13 = fig.add_subplot(6,3,13)
ax14 = fig.add_subplot(6,3,14)
ax15 = fig.add_subplot(6,3,15)
ax16 = fig.add_subplot(6,3,16)
ax17 = fig.add_subplot(6,3,17)
categories = ['Agriculture','Architecture','Art and Performance',
'Biology','Business','Communications and Journalism',
'Computer Science','Education','Engineering',
'English','Foreign Languages','Health Professions',
'Math and Statistics','Physical Sciences','Psychology',
'Public Administration','Social Sciences and History']
ax = [ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8,ax9,ax10,ax11,ax12,ax13,ax14,ax15,ax16,ax17]
for i in range(len(categories)):
ax[i].plot(df['Year'],df[categories[i]],c='red',label='Women')
ax[i].plot(df['Year'],100-df[categories[i]],c='blue',label='Women')
ax[i].set_title(categories[i])
ax[i].set_ylim(0,100)
plt.tight_layout()
plt.savefig('categories.jpeg')
plt.show()
All Playlist of this youtube channel
=======
1. Data Preprocessing in Machine Learning
• Data Preprocessing in Machine Learnin...
2. Confusion Matrix in Machine Learning, ML, AI
• Confusion Matrix in Machine Learning,...
3. Anaconda, Python Installation, Spyder, Jupyter Notebook, PyCharm, Graphviz
• Anaconda | Python Installation | Spyd...
4. Cross Validation, Sampling, train test split in Machine Learning
• Cross Validation | Sampling | train t...
5. Drop and Delete Operations in Python Pandas
• Drop and Delete Operations in Python ...
6. Matrices and Vectors with python
• Matrices and Vectors with python
7. Detect Outliers in Machine Learning
• Detect Outliers in Machine Learning
8. TimeSeries preprocessing in Machine Learning
• TimeSeries preprocessing in Machine L...
9. Handling Missing Values in Machine Learning
• Handling Missing Values in Machine Le...
10. Dummy Encoding Encoding in Machine Learning
• Label Encoding, One hot Encoding, Dum...
11. Data Visualisation with Python, Seaborn, Matplotlib
• Data Visualisation with Python, Matpl...
12. Feature Scaling in Machine Learning
• Feature Scaling in Machine Learning
13. Python 3 basics for Beginner
• Python | Python 3 Basics | Python for...
14. Statistics with Python
• Statistics with Python
15. Sklearn Scikit Learn Machine Learning
• Sklearn Scikit Learn Machine Learning
16. Python Pandas Dataframe Operations
• Python Pandas Dataframe Operations
17. Linear Regression, Supervised Machine Learning
• Linear Regression | Supervised Machin...
18 Interiew Questions on Machine Learning and Data Science
• Interview Question for Machine Learni...
19. Jupyter Notebook Operations
• Jupyter and Spyder Notebook Operation...
Auf dieser Seite können Sie das Online-Video Visualize Plot and Subplots using Matplotlib and Python - P1 mit der Dauer stunde minuten sekunde in guter Qualität ansehen, das der Benutzer technologyCult 16 Februar 2018 hochgeladen hat, den Link mit Freunden und Bekannten teilen, dieses Video wurde auf Youtube bereits 5,563 Mal angesehen und es wurde von 26 den Zuschauern gefallen. Viel Spaß beim Betrachtenden Zuschauern gefallen!
