Python/Pandas: Convert Month Int to Month Name

python/pandas: convert month int to month name

You can do this efficiently with combining calendar.month_abbr and df[col].apply()

import calendar
df['Month'] = df['Month'].apply(lambda x: calendar.month_abbr[x])

Convert month name into number and join it with year in python dataframe

You can use pd.to_datetime and concat like this

df['month_year'] = pd.to_datetime(df.Month, format='%B').dt.month.astype(str) +"_"+ df.Year
df['month_year']
#output
0    1_2019
1    2_2021
2    3_2021
Name: month_year, dtype: object

Update from comment:

Not sure why you get float, but you can try to convert it explicitly to int by adding astype(int) before string

pd.to_datetime(df.Month , format='%B').dt.month.astype(int).astype(str) +"_"+ df.Year

Convert month number to name in python pandas df

You can use pd.Series.dt.strftime.

Python's strftime directives is a useful resource for constructing datetime string formats.

import pandas as pd
from io import StringIO

mystr = StringIO("""Date
01-01-2018 
02-02-2018
03-04-2018""")

# if necessary, read data and convert to datetime
df = pd.read_csv(mystr)
df['Date'] = pd.to_datetime(df['Date'], dayfirst=True)

# apply string formatting
df['Date'] = df['Date'].dt.strftime('%d-%b-%Y')

print(df)

          Date
0  01-Jan-2018
1  02-Feb-2018
2  03-Apr-2018

Extract month name from date column pandas

Check this
https://pandas.pydata.org/docs/reference/api/pandas.Series.dt.month_name.html

df['month'] = pd.DatetimeIndex(df['Date']).month_name()

How to convert month number to month name in an array

If I understand your problem correctly, you are getting an error stating: "list indices must be integers or slices, not list".
To circumvent this issue, try:

import calendar
X=[1,2,3]

def int_to_month(x):
    return calendar.month_name[x]

    
Y = [int_to_month(x) for x in X[:]]

This way you can return the month_name for each element in your X list.

The above script should return: ['January', 'February', 'March']

EDIT:

If X is a pandas Series, you may convert it to a list using the to_list method:

import calendar
import pandas as pd

mycolumn1=[1, 2, 3]
mycolumn2=["foo", "bar", "foo"]

mydata = {"col1":mycolumn1, "col2":mycolumn2}
df=pd.DataFrame(data=mydata)

X = df['col1'].to_list()

def int_to_month(x):
    return calendar.month_name[x]

    
Y = [int_to_month(x) for x in X[:]]

month name to month number and vice versa in python

Create a reverse dictionary using the calendar module (which, like any module, you will need to import):

{month: index for index, month in enumerate(calendar.month_abbr) if month}

In Python versions before 2.7, due to dict comprehension syntax not being supported in the language, you would have to do

dict((month, index) for index, month in enumerate(calendar.month_abbr) if month)

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