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Converting date formats - explicit

Let's have a look at one of the dates from the previous exercise.

  • Sale A: 4000 on 14/02/2018

We used the datetime library to identify the day d, month m, and year y which could help us to identify data from datasets with different date formats. However, what about a scenario where we want to convert date formats into a specific format?

In this exercise you will convert Sale A from the format 14/02/2018 to the same date format as Sale B (i.e. 14 February 2018).

We can do this easily with built-in Python functions. Remember, to split a string we can use the .split()method.

The input for this exercise will be the datetime of Sale A.

Cet exercice fait partie du cours

Financial Forecasting in Python

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Instructions

  • Create a variable dt which contains a string representation of the date you want to convert to a new format (i.e. Sale A).
  • Create a dictionary for the months mm, which will specify which month corresponds to which number, in the format {'number':'month name'}.
  • Split the dt string by the character / and assign values to the day, month and year variables.
  • Print the results by concatenating a string using the dictionary for the given month into the new format.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Set the variable for the datetime to convert
dt = '____'

# Create the dictionary for the month values
mm = {'01': '____', '____': 'February', '____': '____'}

# Split the dt string into the different parts
____, ____, year = dt.split('____')

# Print the concatenated date string
print(____ + ' ' + ____[____] + ' ' + ____)
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