Showing posts with label Pandas. Show all posts
Showing posts with label Pandas. Show all posts

Tuesday, 5 October 2021

Operations On Dataframe in Python

Checking data types of each Column in a Data Frame.


  • If you want to check the data type of each column, because whenever you have been given a data, you want to really check what is the structure of the data; that means, which variable has which data type?
  • In, that case you can use dtypes, because that returns a series with the data type of each column and the syntax would be you use dtypes along with the Data Frame name.
  • So, Data Frame.dtypes will give you a series with the data type of each column

Here is the syntax.

Syntax = DataFrame.dtypes

                                      



Count of unique data types

  • So, now we have an overall idea about what are the data types that we are going to work with using the cars_data. 
  • There is also an option where you can get the count of unique data types available in your Data Frame.
  • So, in that case get_dtype_counts, returns the counts of unique data types in the data frame.


Here is the syntax.

Syntax = get_dtype_counts()





Selecting data based on data types

  • So, now we also have an overall idea about the count of unique data types that we are going to handle with. 

  • So, now, we know about how to get the data type of each variables. So, there might be cases where you want to perform the operations only on a numerical data type.

  • Similarly, there can be cases where you are going to work with only categorical data type.



Here is the syntax.

Syntax = pandas.DataFrame.select.dtypes()












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