Pandas offers a wide set of functionality having to do with dates and times, from extracting values to calculating the differences between dates, to time series, to resampling.
Get better at: CSV, dates and times, multi-indexes, plotting, filtering, and grouping
Get better at: CSV, dates and times, multi-indexes, plotting, filtering, and grouping
Get better at: CSV, dates and times, plotting, grouping, multi-indexes, and stack-unstack.
Get better at: CSV, dates and times, plotting, grouping, multi-indexes, and stack-unstack.
Get better at: CSV, multiple files, filtering, regular expressions, dates and times, window functions
Get better at: CSV, multiple files, filtering, regular expressions, dates and times, window functions
Get better at: Excel, dates and times, missing data, grouping, formatting, using "apply", plotting, and regular expressions
Get better at: Excel, dates and times, missing data, grouping, formatting, using "apply", plotting, and regular expressions
Get better at: CSV, memory optimization, formatting, PyArrow, dates and times, and plotting.
Get better at: CSV, memory optimization, formatting, PyArrow, dates and times, and plotting.
Get better at: CSV files, dates and times, joins, plotting, and correlations.
Get better at: CSV files, dates and times, joins, plotting, and correlations.
