Completed
- Use transform method to join values from two rows into a single row
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Solving Real World Data Science Tasks With Python Pandas
Automatically move to the next video in the Classroom when playback concludes
- 1 - Intro
- 2 - Downloading the Data
- 3 - Getting started with the code Jupyter Notebook
- 4 Task #1: Merging 12 csvs into a single dataframe
- 5 - Read single CSV file
- 6 - List all files in a directory
- 7 - Concatenating files
- 8 - Reading in Updated dataframe
- 9 Task #2: Add a Month column
- 10 - Parse string in Pandas cell .str
- 11 - Drop NaN values from df
- 12 - Remove rows based on condition
- 13 Task #3: Add a sales column
- 14 - Another way to convert a column to numeric ints & floats
- 15 Question #1: What was the best month for sales?
- 16 - Visualizing our results with bar chart in matplotlib
- 17 Question #2: What city sold the most product?
- 18 - Add a city column
- 19 - Using the .apply method super useful!!
- 20 - Why do we use the lambda x ?
- 21 - Dropping a column
- 22 - Answering the question using groupby
- 23 - Plotting our results
- 24 Question #3: What time should we display advertisements to maximize the likelihood of purchases?
- 25 - Using to_datetime method
- 26 - Creating hour & minute columns
- 27 - Matplotlib line graph to plot our results
- 28 - Interpreting our results
- 29 Question #4: What products are most often sold together?
- 30 - Finding duplicate values in our DataFrame
- 31 - Use transform method to join values from two rows into a single row
- 32 - Dropping rows with duplicate values
- 33 - Counting pairs of products itertools, collections
- 34 Question #5: What product sold the most? Why do you think it did?
- 35 - Graphing data
- 36 - Overlaying a second Y-axis on existing chart
- 37 - Interpreting our results