## I want to convert the categorical variable to numerical in Python

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I have a dataframe having categorical variables. I want to convert them to the numerical using the following logic:

I have 2 lists one contains the distinct categorical values in the column and the second list contains the values for each category. Now i need to map these values in place of those categorical values.

For Eg:

List_A = ['A','B','C','D','E'] List_B = [3,2,1,1,2]

I need to replace A with 3, B with 2, C and D with 1 and E with 2.

Is there any way to do this in Python.

I can do this by applying multiple for loops but I am looking for some easier way or some direct function if there is any.

Any help is very much appreciated, Thanks in Advance.

Create a mapping dict

List_A = ['A','B','C','D','E',] List_B = [3,2,1,1,2] d=dict(zip(List_A, List_B)) new_list=['A','B','C','D','E','A','B'] new_mapped_list=[d[v] for v in new_list if v in d] new_mapped_list

Or define a function and use map

List_A = ['A','B','C','D','E',] List_B = [3,2,1,1,2] d=dict(zip(List_A, List_B)) def mapper(value): if value in d: return d[value] return None new_list=['A','B','C','D','E','A','B'] map(mapper,new_list)

**Convert categorical data in pandas dataframe,** How do you convert categorical variables to numeric in Python? Encoding categorical variables is an important step in the data science process. Because there are multiple approaches to encoding variables, it is important to understand the various options and how to implement them on your own data sets. The python data science ecosystem has many helpful approaches to handling these problems.

Suppose df is your data frame and "Category" is the name of the column holding your categories:

df[df.Category == "A"] = 3,2, 1, 1, 2 df[(df.Category == "B") | (df.Category == "E") ] = 2 df[(df.Category == "C") | (df.Category == "D") ] = 1

**(Tutorial) Handling Categorical Data in Python,** How do I convert categorical data to numerical data in pandas? Convert A String Categorical Variable To A Numeric Variable. Try my machine learning flashcards or Machine Learning with Python Cookbook.

If you only need to replace values in one list with the values of other and the structure is like the one you say. Two list, same lenght and same position, then you only need this:

list_a = [] list_a = list_b

A more convoluted solution would be like this, with a function that will create a dictionary that you can use on other lists:

# we make a function def convert_list(ls_a,ls_b): dic_new = {} for letter,number in zip(ls_a,ls_b): dic_new[letter] = number return dic_new

This will make a dictionary with the combinations you need. You pass the two list, then you can use that dictionary on other list:

List_A = ['A','B','C','D','E'] List_B = [3,2,1,1,2] dic_new = convert_list(ls_a, ls_b) other_list = ['a','b','c','d'] for _ in other_list: print(dic_new[_.upper()]) # prints 3 2 1 1

cheers

**I want to convert the categorical variable to numerical in Python ,** These are numeric variables that have an infinite number of values or libraries might transform categorical data to numeric automatically Categorical function is used to convert integer or character column to categorical in pandas python. Let’s see how to. Convert column to categorical in pandas python; First let’s create the dataframe

You could use a solution from machine learning scikit-learn module.

OneHotEncoder LabelEncoder

http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

The pandas "hard" way:

https://stackoverflow.com/a/29330853/9799449

**How to convert categorical data to numerical data in python,** Create a mapping dict List_A = ['A','B','C','D','E',] List_B = [3,2,1,1,2] d=dict(zip(List_A, List_B)) new_list=['A','B','C','D','E','A','B'] Handling Categorical Data in Python Learn the common tricks to handle categorical data and preprocess it to build machine learning models! If you are familiar with machine learning, you will probably have encountered categorical features in many datasets.

**Converting categorical data into numbers with Pandas and Scikit ,** How to convert categorical data to numerical data in python | Python Basics Tutorial Duration: 6:15
Posted: Dec 5, 2019 Encoding categorical variables into numeric variables is part of a data scientist’s daily work. I have been wanting to write down some tips for readers who need to encode categorical variables. The techniques in this article are the frequently used techniques in my professional work.

**Categorical encoding using Label-Encoding and One-Hot-Encoder,** We load data using Pandas, then convert categorical columns with DictVectorizer from scikit-learn. Pandas is a popular Python library inspired by data frames in R. It allows easier manipulation of tabular numeric and non-numeric data. For any questions you may have, Google + StackOverflow combo This video demonstrates transforming categorical variables to numerical variables while making a prediction. If you do have any questions with what we covered in this video then feel free to ask

**Categorical Feature Encoding in Python,** In Machine Learning, convert categorical data into numerical data using For example, color feature having values like red, orange, blue, white etc. used Python library) and are used to convert text or categorical data into How to convert categorical data to numerical data in python | Python Basics Tutorial | Computer science with python CBSE Class XI and XII Dataset link - http

##### Comments

- Thanks mad_ this is really helpful and exactly what I am looking for.
- Thanks shweta24 but this will work if I have only 5-6 categories in my column. But in my dataset there are 000's of categories.
`A`

equivalent value should be 3 not 1.- This is not relevant