Linkedin - Python for Marketing

磁力链接/BT种子名称

Linkedin - Python for Marketing

磁力链接/BT种子简介

种子哈希：10169dca586c528393fcfd7d12deb482371a741d
文件大小：309.87M
已经下载：4155次
下载速度：极快
收录时间：2020-03-01
最近下载：2025-10-09

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磁力链接

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API Integration

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文件列表

  • 03 - Loading and Exploring Your Data/03 - Importing Google Analytics data.mp4 16.6 MB
  • 07 - Calculating, Filtering, and Creating New Metrics/02 - Calculating metrics.mp4 14.1 MB
  • 05 - Visualizing Marketing Data in Python/02 - Import, explore, and plot a basic chart.mp4 13.7 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/02 - Fixing Google Analytics page data.mp4 12.2 MB
  • 07 - Calculating, Filtering, and Creating New Metrics/03 - Filtering data.mp4 12.1 MB
  • 08 - Creating Helpful Alerts/04 - Creating alerts with actions.mp4 12.0 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/05 - Rebuilding Google Analytics data.mp4 10.3 MB
  • 05 - Visualizing Marketing Data in Python/13 - Creating a Facebook Ads heatmap in Seaborn.mp4 10.2 MB
  • 06 - Working with Timeseries/02 - Fixing missing values.mp4 10.1 MB
  • 03 - Loading and Exploring Your Data/08 - Plotting Facebook and Google Ads data.mp4 9.9 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/04 - Creating new datasets with Groupby.mp4 9.8 MB
  • 05 - Visualizing Marketing Data in Python/09 - Adding annotations to plots.mp4 9.7 MB
  • 06 - Working with Timeseries/04 - Rolling average plots.mp4 9.4 MB
  • 06 - Working with Timeseries/06 - Adding dynamic annotations to a plot.mp4 9.2 MB
  • 03 - Loading and Exploring Your Data/05 - Importing Facebook and AdWords data.mp4 8.8 MB
  • 05 - Visualizing Marketing Data in Python/05 - Adding x and y labels to a plot.mp4 8.4 MB
  • 08 - Creating Helpful Alerts/03 - Calculating two date ranges.mp4 8.1 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/03 - Preparing data to be grouped.mp4 8.1 MB
  • 03 - Loading and Exploring Your Data/07 - Visualizing Google data.mp4 7.6 MB
  • 05 - Visualizing Marketing Data in Python/03 - Creating Matplotlib subplots.mp4 7.6 MB
  • 05 - Visualizing Marketing Data in Python/04 - Plotting a secondary y-axis.mp4 7.4 MB
  • 05 - Visualizing Marketing Data in Python/12 - Customizing a scatter plot in Seaborn.mp4 7.4 MB
  • 05 - Visualizing Marketing Data in Python/06 - Rotating xticks labels on plot.mp4 6.8 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/06 - Dropping columns.mp4 6.6 MB
  • 03 - Loading and Exploring Your Data/06 - Accessing the Google Trends API.mp4 6.6 MB
  • 06 - Working with Timeseries/05 - Plotting weekly PPC and CPC data.mp4 5.7 MB
  • 06 - Working with Timeseries/03 - Resampling time series data.mp4 5.1 MB
  • 08 - Creating Helpful Alerts/02 - Creating simple alerts.mp4 5.1 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/08 - Merging Google Analytics and Search Console.mp4 5.0 MB
  • 03 - Loading and Exploring Your Data/09 - Visualizing Google Trends data.mp4 4.5 MB
  • 05 - Visualizing Marketing Data in Python/10 - Switching between Matplotlib styles.mp4 4.4 MB
  • 05 - Visualizing Marketing Data in Python/08 - Adding a title to your plot.mp4 4.3 MB
  • 05 - Visualizing Marketing Data in Python/07 - Adding a legend to a plot.mp4 4.2 MB
  • 03 - Loading and Exploring Your Data/02 - Installing Jupyter.mp4 4.2 MB
  • 01 - Introduction/01 - Accelerate your marketing with Python.mp4 4.0 MB
  • 09 - Conclusion/01 - Next steps.mp4 3.7 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/07 - Replacing missing Facebook Ad data.mp4 3.7 MB
  • 02 - The Role of Python in Marketing/02 - Why Python is great for marketers.mp4 3.7 MB
  • 03 - Loading and Exploring Your Data/01 - Introduction to pandas.mp4 3.3 MB
  • 05 - Visualizing Marketing Data in Python/11 - Using a scatter plot in Seaborn.mp4 3.1 MB
  • 03 - Loading and Exploring Your Data/04 - Importing Google Search Console data.mp4 3.0 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/01 - Introduction to data wrangling.mp4 2.3 MB
  • 02 - The Role of Python in Marketing/03 - Why Python is valuable for marketers.mp4 2.2 MB
  • 04 - Cleaning, Wrangling, and Joining Your Data/09 - Saving your data to a CSV.mp4 2.2 MB
  • 05 - Visualizing Marketing Data in Python/01 - Custom visualizations in Python.mp4 2.0 MB
  • Exercise Files/Ex_Files_Python_Marketing.zip 1.9 MB
  • 07 - Calculating, Filtering, and Creating New Metrics/01 - Introduction to calculating and filtering.mp4 1.6 MB
  • 06 - Working with Timeseries/01 - Time series notebook.mp4 1.3 MB
  • 02 - The Role of Python in Marketing/01 - Prerequisites.mp4 1.0 MB
  • 08 - Creating Helpful Alerts/01 - Intro to alert calculations.mp4 612.9 kB
  • 05 - Visualizing Marketing Data in Python/02 - Import, explore, and plot a basic chart.srt 7.2 kB
  • 03 - Loading and Exploring Your Data/03 - Importing Google Analytics data.srt 7.0 kB
  • 04 - Cleaning, Wrangling, and Joining Your Data/02 - Fixing Google Analytics page data.srt 6.4 kB
  • 08 - Creating Helpful Alerts/04 - Creating alerts with actions.srt 6.3 kB
  • 07 - Calculating, Filtering, and Creating New Metrics/03 - Filtering data.srt 5.5 kB
  • 03 - Loading and Exploring Your Data/08 - Plotting Facebook and Google Ads data.srt 5.1 kB
  • 04 - Cleaning, Wrangling, and Joining Your Data/04 - Creating new datasets with Groupby.srt 4.9 kB
  • 05 - Visualizing Marketing Data in Python/09 - Adding annotations to plots.srt 4.8 kB
  • 05 - Visualizing Marketing Data in Python/13 - Creating a Facebook Ads heatmap in Seaborn.srt 4.7 kB
  • 05 - Visualizing Marketing Data in Python/05 - Adding x and y labels to a plot.srt 4.3 kB
  • 06 - Working with Timeseries/04 - Rolling average plots.srt 4.3 kB
  • 03 - Loading and Exploring Your Data/07 - Visualizing Google data.srt 4.2 kB
  • 05 - Visualizing Marketing Data in Python/04 - Plotting a secondary y-axis.srt 4.1 kB
  • 03 - Loading and Exploring Your Data/05 - Importing Facebook and AdWords data.srt 3.8 kB
  • 04 - Cleaning, Wrangling, and Joining Your Data/03 - Preparing data to be grouped.srt 3.6 kB
  • 03 - Loading and Exploring Your Data/06 - Accessing the Google Trends API.srt 3.2 kB
  • 06 - Working with Timeseries/03 - Resampling time series data.srt 3.1 kB
  • 08 - Creating Helpful Alerts/02 - Creating simple alerts.srt 2.5 kB
  • 02 - The Role of Python in Marketing/02 - Why Python is great for marketers.srt 2.4 kB
  • 03 - Loading and Exploring Your Data/09 - Visualizing Google Trends data.srt 2.3 kB
  • 01 - Introduction/01 - Accelerate your marketing with Python.srt 2.2 kB
  • 04 - Cleaning, Wrangling, and Joining Your Data/07 - Replacing missing Facebook Ad data.srt 1.7 kB
  • 05 - Visualizing Marketing Data in Python/10 - Switching between Matplotlib styles.srt 1.6 kB
  • 05 - Visualizing Marketing Data in Python/01 - Custom visualizations in Python.srt 1.2 kB
  • 07 - Calculating, Filtering, and Creating New Metrics/01 - Introduction to calculating and filtering.srt 1.2 kB
  • 06 - Working with Timeseries/01 - Time series notebook.srt 846 Bytes
  • 08 - Creating Helpful Alerts/01 - Intro to alert calculations.srt 488 Bytes

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