Pandas fundamentals every data scientist needs to know - Part 1

Learn the most important Pandas fundamentals to boost your performance and start coding like a pro in no time!

Pandas can be intimidating at first but it's such a great library with so much potential and so much flexibility. In this series, I will talk about the main working principles of Pandas I have picked up over the years. These will boost your coding performance as they will help you understand how your code works in the background.

In this part we talk about Dataframe and Series objects and how and why they are integral to the workings of Pandas.

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[nathaneckel]

Saving us time energy and tears on this incredible explanation, thank you once again @Misra :) Really appreciate that you identified and gave us a simple framework to think about Pandas.

[anlelmastas]

After NumPy, as a beginner of Pandas, I really like your "detailed" explanation of each lines. Waiting for other parts like this. Thanks^^

[LNMLucasMasiero]

Extra Tip:
This are different ways of accesing to a df.
The df is 3 columns of 'a', 'b', 'c' and 3 rows of 'x', 'y', 'z'

import pandas as pd

a = {
'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9], }

df = pd.DataFrame(a, index=['x', 'y', 'z'])


#INDEXING
#Row #Column ►►► Format
print(df.iloc[0]); print(df.iloc[:, 1])# Serie
print(df.iloc[[0]]); print(df.iloc[:, [1]])# DataFrame


#NAMING
#Row #Column ►►► Format
print(df.loc['x']); print(df.loc[:, 'a']); print(df['a'])# Serie
print(df.loc[['x']]); print(df.loc[:, ['a']]); print(df[['a']])# DataFrame

[higiniofuentes]

Can we install Jupyter in a website? Or there are a website to work with panda's?
Thank you!

[higiniofuentes]

May I ask how to install pandas?
Thank you!

[jainamshah]

Hi, Is there a video on how to export the datasets once it is cleaned and exporting it to overright the existing data, so we can do visualisation through tableau/powerBI on it