👉If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter.
“The 22 Most-Used Python Packages in the World” by Erik van Baaren https://link.medium.com/urafNGaY36
Medium
The 22 Most-Used Python Packages in the World
Educational and surprising insights into how Python is used
A beginner-friendly list of data science projects
1) Rainfall in India
Project type: Visualization
Link to dataset : https://www.kaggle.com/rajanand/rainfall-in-india
2) Global Suicide Rates
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016
3) Summer Olympic Medals
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/divyansh22/summer-olympics-medals
4) World Happiness Report
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/unsdsn/world-happiness
5) Pollution in the United States
Project type: Visualization
Link to dataset : https://www.kaggle.com/sogun3/uspollution
6) Nutrition Facts for McDonald’s Menu
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/mcdonalds/nutrition-facts
7) Red Wine Quality
Project type: Prediction Modeling
Link to dataset : https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009
1) Rainfall in India
Project type: Visualization
Link to dataset : https://www.kaggle.com/rajanand/rainfall-in-india
2) Global Suicide Rates
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016
3) Summer Olympic Medals
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/divyansh22/summer-olympics-medals
4) World Happiness Report
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/unsdsn/world-happiness
5) Pollution in the United States
Project type: Visualization
Link to dataset : https://www.kaggle.com/sogun3/uspollution
6) Nutrition Facts for McDonald’s Menu
Project type: Exploratory Data Analysis
Link to dataset : https://www.kaggle.com/mcdonalds/nutrition-facts
7) Red Wine Quality
Project type: Prediction Modeling
Link to dataset : https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009
Kaggle
Rainfall in India
Sub-division wise monthly data for 115 years from 1901-2015.
😃Huge List of Free Machine Learning resources like 620K+ Datasets, 150+ Notebooks, & many more......
Link : https://aihub.cloud.google.com/u/0/
Link : https://aihub.cloud.google.com/u/0/
What is the output of the following code snippet?
func = lambda x: return x print(func(2))
func = lambda x: return x print(func(2))
Anonymous Quiz
6%
x
30%
SyntaxError
21%
2.0
41%
2
3%
0
“How to start writing Data Science blogs?” by Rashi Desai https://link.medium.com/PCRKp4sZ76
Medium
How to start writing Data Science blogs?
Thinking of blogging on Data Science? This one is for you.
👍 Best TED Talks for Data Science
1. How not to be ignorant about the world
Topic: Data Visualization
Speaker: Hans Rosling, author of “Factfulness”
Link : https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seen?language=en
2. The Beauty of Data Visualization
Topic: Data Visualization
Speaker: David McCandless, renowned data journalists.
Link : https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization?language=en
3. Three ways to spot a bad statistic
Topic: Statistics
Speaker: Mona Chalabi, data journalist
Link : https://www.ted.com/talks/mona_chalabi_3_ways_to_spot_a_bad_statistic?referrer=playlist-making_sense_of_too_much_data
4. Big Data is better data
Topic: Big Data
Speaker: Kenneth Cukier, data analyst for The Economist
Link : https://www.ted.com/talks/kenneth_cukier_big_data_is_better_data
5. The human insight missing from Big Data
Topic: Big Data
Speaker: Tricia Wang, global tech ethnographer
Link : https://www.ted.com/talks/tricia_wang_the_human_insights_missing_from_big_data?referrer=playlist-making_sense_of_too_much_data
6. Your company’s data could end world hunger
Topic: The value of data
Speaker: Dr. Mallory Freeman, Lead Data Scientist in the UPS Advanced Technology Group
Link : https://www.ted.com/talks/mallory_freeman_your_company_s_data_could_help_end_world_hunger?referrer=playlist-making_sense_of_too_much_data
7. Who Controls the World
Topic: Complexity Theory
Speaker: James B. Glattfelder, Swiss Scientist
Link : https://www.ted.com/talks/james_b_glattfelder_who_controls_the_world?language=en
1. How not to be ignorant about the world
Topic: Data Visualization
Speaker: Hans Rosling, author of “Factfulness”
Link : https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seen?language=en
2. The Beauty of Data Visualization
Topic: Data Visualization
Speaker: David McCandless, renowned data journalists.
Link : https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization?language=en
3. Three ways to spot a bad statistic
Topic: Statistics
Speaker: Mona Chalabi, data journalist
Link : https://www.ted.com/talks/mona_chalabi_3_ways_to_spot_a_bad_statistic?referrer=playlist-making_sense_of_too_much_data
4. Big Data is better data
Topic: Big Data
Speaker: Kenneth Cukier, data analyst for The Economist
Link : https://www.ted.com/talks/kenneth_cukier_big_data_is_better_data
5. The human insight missing from Big Data
Topic: Big Data
Speaker: Tricia Wang, global tech ethnographer
Link : https://www.ted.com/talks/tricia_wang_the_human_insights_missing_from_big_data?referrer=playlist-making_sense_of_too_much_data
6. Your company’s data could end world hunger
Topic: The value of data
Speaker: Dr. Mallory Freeman, Lead Data Scientist in the UPS Advanced Technology Group
Link : https://www.ted.com/talks/mallory_freeman_your_company_s_data_could_help_end_world_hunger?referrer=playlist-making_sense_of_too_much_data
7. Who Controls the World
Topic: Complexity Theory
Speaker: James B. Glattfelder, Swiss Scientist
Link : https://www.ted.com/talks/james_b_glattfelder_who_controls_the_world?language=en
Ted
The best stats you've ever seen
You've never seen data presented like this. With the drama and urgency of a sportscaster, statistics guru Hans Rosling debunks myths about the so-called "developing world."
List a is defined as follows:
a = [1, 2, 3, 4, 5] Select all of the following statements that remove the middle element 3 from a so that it equals [1, 2, 4, 5]:
a = [1, 2, 3, 4, 5] Select all of the following statements that remove the middle element 3 from a so that it equals [1, 2, 4, 5]:
Anonymous Poll
58%
a.remove(3)
21%
a[2] = [ ]
19%
a[2:3] = [ ]
50%
del a[2]
7%
a[2:2] = [ ]
❤1
a, b, c = (1, 2, 3, 4, 5, 6, 7, 8, 9)[1::3]
Following execution of this statement, what is the value of b:
Following execution of this statement, what is the value of b:
Anonymous Quiz
19%
6
32%
2
26%
4
23%
5
What is the result of this statement:
>>> z = {'b', 'a', 'r'} & set('qux') . >>> print(z)
>>> z = {'b', 'a', 'r'} & set('qux') . >>> print(z)
Anonymous Quiz
9%
{ )
22%
set( )
49%
{'q', 'r', 'x', 'u', 'b', 'a'}
19%
{'b', 'r', 'a'}