There are many different ways to reshape a pandas dataframe from long to wide form. But the pivot_table() method is the most flexible and probably the only one you need to use once you learn it well, just like how you only need to learn one method melt to reshape from wide to long (see my other post below).
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Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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In this post, we will learn about pandas’ data structures/objects. Pandas provide two type of data structures:-
Pandas Series is a one dimensional indexed data, which can hold datatypes like integer, string, boolean, float, python object etc. A Pandas Series can hold only one data type at a time. The axis label of the data is called the index of the series. The labels need not to be unique but must be a hashable type. The index of the series can be integer, string and even time-series data. In general, Pandas Series is nothing but a column of an excel sheet with row index being the index of the series.
Pandas dataframe is a primary data structure of pandas. Pandas dataframe is a two-dimensional size mutable array with both flexible row indices and flexible column names. In general, it is just like an excel sheet or SQL table. It can also be seen as a python’s dict-like container for series objects.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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Pandas tutorial covering the basics of DataFrame. This is a very good starting point to learn Pandas DataFrame. We will go through the definition, learn useful methods and attributes that will make you comfortable with pandas DataFrame and how to manipulate it. Within this tutorial you will learn:
0:00 - Intro
0:10 - Presentation: DataFrame definition
0:40 - Presentation: Recommended approach to learn pandas
1:43 - Create DataFrame from Pandas I/O API
3:44 - Create DataFrame manually
7:40 - Methods: head, tail and sample
8:53 - Attributes: index, column and values
11:07 - Attributes: shape and dtypes
12:08 - Method: info
12:55 - Method: describe
14:57 - Accessing columns: bracket and dot notation
17:18 - Creating and deleting columns
18:53 - Arithmetic operation with columns (panda series)
22:10 - Next video
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Pandas is used for data manipulation, analysis and cleaning.
What are Data Frames and Series?
Dataframe is a two dimensional, size mutable, potentially heterogeneous tabular data.
It contains rows and columns, arithmetic operations can be applied on both rows and columns.
Series is a one dimensional label array capable of holding data of any type. It can be integer, float, string, python objects etc. Panda series is nothing but a column in an excel sheet.
s = pd.Series([1,2,3,4,56,np.nan,7,8,90])
How to create a dataframe by passing a numpy array?
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