Convert hh:mm:ss to minutes using python pandas

by

Assuming this is a string column you can use the str.split method:

In [11]: df['time taken'].str.split(':')
Out[11]:
0    [02, 08, 00]
1    [02, 05, 00]
2    [02, 55, 00]
3    [03, 42, 00]
4    [01, 12, 00]
5    [01, 46, 00]
6    [03, 22, 00]
7    [03, 36, 00]
Name: time taken, dtype: object

And then use apply:

In [12]: df['time taken'].str.split(':').apply(lambda x: int(x[0]) * 60 + int(x[1]))
Out[12]:
0    128
1    125
2    175
3    222
4     72
5    106
6    202
7    216
Name: time taken, dtype: int64

More Related Contents:

  1. Delete a column from a Pandas DataFrame
  2. Convert Python dict into a dataframe
  3. What is the most efficient way to loop through dataframes with pandas?
  4. Format / Suppress Scientific Notation from Pandas Aggregation Results
  5. Split cell into multiple rows in pandas dataframe
  6. Python Pandas Error tokenizing data
  7. Handling Variable Number of Columns with Pandas – Python
  8. Pandas: Converting to numeric, creating NaNs when necessary
  9. Pandas, groupby and count
  10. No module named ‘pandas._libs.tslibs.timedeltas’ in PyInstaller
  11. Use groupby in Pandas to count things in one column in comparison to another
  12. Combining two Series into a DataFrame in pandas
  13. Take multiple lists into dataframe
  14. Reset color cycle in Matplotlib
  15. Adding two pandas dataframes
  16. Use index in pandas to plot data
  17. How to find which columns contain any NaN value in Pandas dataframe
  18. Python pandas: Keep selected column as DataFrame instead of Series
  19. How to group pandas DataFrame entries by date in a non-unique column
  20. “Series objects are mutable and cannot be hashed” error
  21. pandas: combine two columns in a DataFrame
  22. python pandas read_csv delimiter in column data
  23. Numpy isnan() fails on an array of floats (from pandas dataframe apply)
  24. Can you format pandas integers for display, like `pd.options.display.float_format` for floats?
  25. Why does max() sometimes return nan and sometimes ignores it?
  26. How to fill the missing record of Pandas dataframe in pythonic way?
  27. Pandas analogue to SQL MINUS / EXCEPT operator, using multiple columns
  28. plot different color for different categorical levels
  29. Pandas Groupby Agg Function Does Not Reduce
  30. Pandas groupby and make set of items

Leave a Comment