Though Jupyter Notebook has been continuously improved, still its basic design doesn’t satisfy the majority of developers who got used to modern feature-rich IDEs. This is where notebook extensions (aka nbextensions) come in. Being not officially related to the Jupyter team, they still can make data scientist’s life much-much easier. Below I’ll describe how to install and enable Jupyter Notebook extensions with conda.
Continue reading How to manage Jupyter Notebook extensionsCategory: Data Preprocessing
How to Convert Pandas Column to DateTime
Suppose, you have a column named ‘date’ in pandas data frame df. It represents a date and/or time, but pandas thinks it just a string (or an object) and you can’t apply all date/time-specific operations on it. The solution is simple:
df['date'] = pandas.to_datetime(df['date'])
though the to_datetime function is smart enough to recognize date/time format, you can add your own format specification:
df['date'] = pandas.to_datetime(df['date'], format='%d%b%Y:%H:%M:%S.%f')
Early Data Analysis with Pandas
How to get a brief view on what data poses? Continue reading Early Data Analysis with Pandas