Python Pandas for Data Analysis: The Fundamentals

Unlock the power of data manipulation and analysis with Python Pandas in this comprehensive tutorial. Whether you're a beginner or an experienced programmer, this video will take you on a journey through the fundamental concepts of working with DataFrames. From creating and manipulating data to advanced aggregation techniques, you'll learn how to extract valuable insights and key statistics to make informed decisions. Dive into real-world examples and discover how to handle missing values, filter, and sort data, perform group-by operations, and more. Join us to master the art of data analysis and boost your Python skills today!

Python Pandas, Data Analysis, Data Manipulation, DataFrame, Python Programming, Data Cleaning, Aggregation Techniques, Missing Values, Filtering Data, Sorting Data, Group By, Real-world Examples

[austinb]

Bro taught me more about Python/R than my masters teacher did in 6 months

[TobysDataDigest]

To those eagle-eyed viewers, you'll notice that the ID column continues sequentially and then stops, with the last few values being NaN. Here's how you can impute those missing ID values using Python pandas:

# Get the maximum existing ID
max_existing_id = df['ID'].max()

# Initialise a variable to keep track of the last valid ID
last_id = max_existing_id if pd.notnull(max_existing_id) else 0

# Loop through each row in the DataFrame
for i in range(len(df)):
# Check if the 'ID' value in the current row is missing (NaN)
if pd.isnull(df.at[i, 'ID']):
# Increment the last valid ID by 1 to generate the next missing ID
last_id += 1
# Fill the missing 'ID' value in the current row with the generated ID
df.at[i, 'ID'] = last_id

[okok-sccx]

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please make videos on machine learning topics - linear regression, classification and everything else

Thank you so much once again ❤

[abal]

Great video. I will be sure to check out your channel!

[liamfinch]

Hey man love the video and subscribed! Would it be possible to share the file?