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A Python-based tool that reformats multiple date formats into a single format for later use.
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dateCleanse.py

dateCleanse.py converts a variety of date formats and to a single, common format: MM/DD/YYYY.

Development pace will coincide with its frequency of use for date cleansing in different applications, but this tool is ready for use. Written and tested in Python 3.4.3.

Currently Supported Date Formats

  • MM/YYYY
  • YYYY/MM
  • YYYY-MM
  • *YY-MM
  • DDDDD (days since 01/01/1900)
  • YY/MM
  • YY-MM
  • YYMM
  • YYYY
  • M-YY
  • M/YY
  • YY-M
  • MYY
  • YYYY-M-DD HH:MM:SS

Note that two-digit years are assumed to occur post year 2000 and that all dates are assumed to occur post 1930.

Date Formats for Future Release

We do not have any other date formats currently planned for future release. If you'd like to see a different date format included for future release, please let us know or submit a pull request.

How-To

Export a single column from your data frame or your vector of dates into the directory input_data. If you are using R, you can export the files to that directory individually as follows:

# include the dates you wish to reformat in the directory titled input_data
setwd("C:/user/folder/input_data")
# repeat the following write command for all the files you want to reformat
write.csv(dates, "name_of_file.csv", row.names=FALSE, quote=FALSE)

Your working directory will be different depending on your system configuration. Ensure that row names and quotes are not included from the R output. Then, simply fire up your favorite Python IDE and hit run. Or from the command line, type:

python dateCleanse.py

The script will ask for the path to the directory which contains the dates to be reformatted. If you placed your name_of_file.csv file in the same directory, simply type:

input_data

and hit enter (this step may seem trivial but allows for flexibility if your files are in a different directory).

The script will begin reformatting the date values and show several progress bars. Once the process complete, cleansed dates are stored in a new file called newDates.csv, contained in a new directory titled output_data.

Non-native Dependencies

  • tqdm
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