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Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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17: Why Pandas is the new Excel

16:37
 
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Manage episode 245389209 series 2550866
Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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.

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support
  continue reading

27 에피소드

Artwork
icon공유
 
Manage episode 245389209 series 2550866
Sanket Gupta에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sanket Gupta 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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.

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support
  continue reading

27 에피소드

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