How to Extract Month and Year from Date String in a Pandas DataFrame [All Method]️
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It’s also a question How to Extract Month and Year from Date String in a Pandas DataFrame? What should you do if you come across a code error! Let’s get started on fixing it.
Question: What is the best way to approach this problem? Answer: Check out this blog code to learn how to fix errors How to Extract Month and Year from Date String in a Pandas DataFrame. Question:”What should you do if you run into code errors?” Answer:”By following this blog, you can find a solution.”
Suppose we have a Date column in my Pandas DataFrame.
Date Num
1950-01-01 1.50
1950-02-01 1.50
1950-03-01 1.50
1950-04-01 1.50
Let’s say we want to create a Year and Month column from Date, but it’s a string.
Convert Date string using DateTimeIndex
We can store the values in our Date column with DateTimeIndex, which is simply a collection of timestamp objects with varying UTC offsets.
date = pd.DatetimeIndex(df['Date'])
Extract month and year
We can then extract the month and year (or day or whatever attributes we want) from this DateTimeIndex.
df['Year'] = date.year
df['Month'] = date.month
Convert Date string using Series.dt
Instead of using pd.DateTimeIndex, we can simply use .dt on any datetimelike column.
date = df['Date'].dt
Extract month and year
Extracting the month and year would be the same as with the DateTimeIndex.
df['Year'] = date.year
df['Month'] = date.month
Revise the code and make it more robust with proper test case and check an error there before implementing into a production environment.
Final Note: Try to Avoid this type of mistake(error) in future!
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