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17: Why Pandas is the new Excel
The Data Life Podcast is a podcast where we talk all-about real life experiences with data and data science science tools, techniques, models and personalities.
In this episode, we will talk about how Pandas is becoming a tool of choice for many data scientists for doing their data analysis work. We will explore how Pandas wins over Excel in several key areas that are important for businesses today:
1) Large dataset sizes
2) Different kinds of input formats such as JSON, CSV, HTML, SQL etc
3) Complex business logic
4) Linking data analysis work to websites and databases
5) Cost
Pandas has lots of helpful functions such as read_csv, read_json, read_sql that allow easy input of data into dataframes. DataFrames have several useful methods like "describe", "value_counts", "groupby", "loc" and more that allow easy understanding of your dataset. It also supports plotting out of the box with "plot" method.
We also cover how Pandas differs from SQL in things like ease of handling time series data, visualizations and more.
Tune in to the episode to learn more about how Pandas might be the tool for your data analysis needs to take your business to next level!
Fantastic Resources:
1) Book by Pandas creator Wes McKinney: https://www.amazon.com/dp/1491957662/?tag=omnilence-20
2) Great workshop video by Kevin Markham in PyCon: https://www.youtube.com/watch?v=0hsKLYfyQZc
3) Input output methods for Pandas: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html
4) Comparison of some operations of Pandas with SQL https://pandas.pydata.org/pandas-docs/stable/getting_started/comparison/comparison_with_sql.html
Thanks for listening! Please consider supporting this podcast from the link in the end.
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By Sanket Gupta
5
55 ratings
The Data Life Podcast is a podcast where we talk all-about real life experiences with data and data science science tools, techniques, models and personalities.
In this episode, we will talk about how Pandas is becoming a tool of choice for many data scientists for doing their data analysis work. We will explore how Pandas wins over Excel in several key areas that are important for businesses today:
1) Large dataset sizes
2) Different kinds of input formats such as JSON, CSV, HTML, SQL etc
3) Complex business logic
4) Linking data analysis work to websites and databases
5) Cost
Pandas has lots of helpful functions such as read_csv, read_json, read_sql that allow easy input of data into dataframes. DataFrames have several useful methods like "describe", "value_counts", "groupby", "loc" and more that allow easy understanding of your dataset. It also supports plotting out of the box with "plot" method.
We also cover how Pandas differs from SQL in things like ease of handling time series data, visualizations and more.
Tune in to the episode to learn more about how Pandas might be the tool for your data analysis needs to take your business to next level!
Fantastic Resources:
1) Book by Pandas creator Wes McKinney: https://www.amazon.com/dp/1491957662/?tag=omnilence-20
2) Great workshop video by Kevin Markham in PyCon: https://www.youtube.com/watch?v=0hsKLYfyQZc
3) Input output methods for Pandas: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html
4) Comparison of some operations of Pandas with SQL https://pandas.pydata.org/pandas-docs/stable/getting_started/comparison/comparison_with_sql.html
Thanks for listening! Please consider supporting this podcast from the link in the end.