1/ #Pandas is the go-to library that you need for #datawrangling for your #datascience projects when coding in #Python.
ππ§΅π See thread below
ππ§΅π See thread below
2/ Why Do We Need Pandas?
The Pandas library has a large set of features that will allow you to perform tasks from the first intake of raw data, its cleaning and transformation to the final curated form in order to validate hypothesis testing and machine learning model building.
The Pandas library has a large set of features that will allow you to perform tasks from the first intake of raw data, its cleaning and transformation to the final curated form in order to validate hypothesis testing and machine learning model building.
3/ Basics of Pandas - 1. Pandas Objects
Pandas allows us to work with tabular datasets. The basic data structures of Pandas that consists of 3 types: Series, DataFrame and DataFrameIndex. The first 2 are data structures while the latter serves as a point of reference.
Pandas allows us to work with tabular datasets. The basic data structures of Pandas that consists of 3 types: Series, DataFrame and DataFrameIndex. The first 2 are data structures while the latter serves as a point of reference.
4/ Basics of Pandas - 2. Series
Pandas Series is a one-dimensional array with the ability to be labeled. A Series can hold an integer, float, string, python object, etc. At a high-level, a Series can be thought of as a column in Microsoft Excel. It's similar to the NumPy array.
Pandas Series is a one-dimensional array with the ability to be labeled. A Series can hold an integer, float, string, python object, etc. At a high-level, a Series can be thought of as a column in Microsoft Excel. It's similar to the NumPy array.
5/ Basics of Pandas - 3. DataFrame
The Pandas DataFrame is a two-dimensional array of dataframes. It is similar to the spreadsheet in Microsoft Excel.
The Pandas DataFrame is a two-dimensional array of dataframes. It is similar to the spreadsheet in Microsoft Excel.
6/ Basics of Pandas - 4. Index
Pandas Index is an inherent property of Series and DataFrame objects. It serves as a point of reference as to which rows and/or columns to perform operations on.
Pandas Index is an inherent property of Series and DataFrame objects. It serves as a point of reference as to which rows and/or columns to perform operations on.
7/ Conclusion 1 of 2
Pandas is a core component in any data science workflow. To a beginner starting out, learning to use Pandas may seem like a formidable task owing to large collection of Pandas functions that are available.
Pandas is a core component in any data science workflow. To a beginner starting out, learning to use Pandas may seem like a formidable task owing to large collection of Pandas functions that are available.
8/ Conclusion 2 of 2
In summary, we have taken a high-level overview of the Pandas library, considered the importance of data wrangling, learned about the basic data structures in Pandas.
In summary, we have taken a high-level overview of the Pandas library, considered the importance of data wrangling, learned about the basic data structures in Pandas.
9/ Contents of this thread came from my full blog.
Check it out! π
towardsdatascience.com/how-to-master-β¦
Check it out! π
towardsdatascience.com/how-to-master-β¦
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