You can use the following code to convert the month number to month name in Pandas.

Full name:

df['date'].dt.month_name()

3 letter abbreviation of the month:

df['date'].dt.month_name().str[:3]

Next, you'll see example and steps to get the month name from number:

Step 1: Read a DataFrame and convert string to a DateTime

For example, let's have a DataFrame with a date column inside which is stored a string.

DataFrame and steps are explained here - How to Search and Download Kaggle Dataset to Pandas DataFrame or if you use the notebook:

import pandas as pd
df = pd.read_csv('../data/medium_data.csv.zip')
df

In case of a date which is stored as a string you can convert it to a datetime by:

df['date'] = pd.to_datetime(df['date'])

the data is shown below:

title date claps
A Beginner’s Guide to Word Embedding with Gensim Word2Vec Model 2019-05-30 850
Hands-on Graph Neural Networks with PyTorch & PyTorch Geometric 2019-05-30 1100
How to Use ggplot2 in Python 2019-05-30 767
Databricks: How to Save Files in CSV on Your Local Computer 2019-05-30 354
A Step-by-Step Implementation of Gradient Descent and Backpropagation 2019-05-30 211

Step 2: Convert Month Number to Full Month Name

There are several different ways to get a full month name in Pandas and Python.

First we will show the built in dt method - .dt.month_name():

df['month_full'] = df['date'].dt.month_name()

This will return the full month name as a new column:

title date claps month_full
How to Get and Keep Clients as a Freelancer 2019-05-27 965 May
A Battle for the Soul of BreadTube Is Currently Taking Place 2019-07-29 105 July
<strong class="markup--strong markup--h3-strong">Business Opportunity: The Colombian Oils and Lubricants Market</strong> 2019-02-09 0 February
How to know your price is right 2019-12-05 102 December
3 Types of Reports That Business Analysts Need to Learn 2019-09-18 309 September

Step 3: Convert Month Number to Month abbreviation

In this step instead of the full month name we will get an abbreviation of the first 3 letters of the name. It's going to use the same method plus str slicing:

df['month_short'] = df['date'].dt.month_name().str[:3]

The result are short names like:

Jul
Mar
Mar
Dec
Aug

Step 4: Convert Month Number to Month name with strftime

One more way to convert a month to it's name is by using the method - strftime. This can be done by:

df['date'].dt.strftime('%b')

this will return short names as:

Jul
Mar
Mar
Dec
Aug

For a full month name you can use %B:

df['date'].dt.strftime('%B')

output:

July
March

Step 5: Convert Month Number to custom name with mapping

Finally, what if you like to get custom labels or month names in different languages like Spanish or French.

Then you can apply a custom mapping with apply:

import pandas as pd

month_labels = {1: 'I', 2: 'II', 3: 'III', 4: 'IV', 5: 'V', 6: 'VI', 7: 'VII', 8: 'VIII',
                9: 'IX', 10: 'X', 11: 'XI', 12: 'XII'}


df['month'] = df['date'].dt.month
df['month'].apply(lambda x: month_labels[x])

Above you can find the mapping - month_labels which can be updated to suit your needs.

You need also to get the month number by df['date'].dt.month

result is:

III
VII

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