Description: In the 24th installment of our Python Pandas Tutorial series, we focus on refining your data manipulation skills by exploring the .loc accessor for retrieving specific rows based on index labels. Join us as we demystify the intricacies of data selection in Pandas, guiding you through practical examples and scenarios where .loc proves invaluable. Learn how to harness the full potential of this accessor to access and manipulate data efficiently, unlocking precise control over your DataFrame. Elevate your Pandas expertise and streamline your data analysis workflow with this comprehensive tutorial on utilizing the .loc accessor for row selection.
Chapters:
1:32 - Get the first row of a column in the pandas dataframe using df.loc[0]
3:00 - Assign an existing column of pandas.DataFrame to index (row label) by using set_index()
4:15 - Access a specified index value with .loc property from the unique valued column
6:06 - Access a specified index value from duplicated column
7:50 - 9:30 - Extract the certain rows from numeric labeled index with .loc accessor
9:42 - 14:13 - Extract specific rows from string labeled index with .loc accessor
14:20 - Output the dataset by giving multiple parameters with .loc accessor in pandas
Source:
https://github.com/Rruhid/data
#python #ai #bigdata #dataanalysis #datascience #dataanalytics #pandas
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Python Pandas Tutorial
.loc Accessor
DataFrame Indexing
Data Manipulation
Data Analysis
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