With the new release of buckaroo, df.head()
is obsolete. I have worked to make Buckaroo usable as the default table visualization for pandas dataframes. It does this through sensible defaults and down sampling.
The default process of investigating a new dataset with pandas and jupyter is to load a dataframe from csv, parquet, or some other data source. The next step is df.head()
or df.describe()
, if you just type df
pandas will try to show the first 5 rows and last 5 rows, and possibly all of the columns. Pandas needs to limit the output to avoid overwhelming a notebook with text output, and causing performance issues. Soon you will find yourself looking up pd.options.display.width = 0
or pd.options.display.max_rows = 500
with pd.option_context('display.max_rows', None, 'display.max_columns', None):
print (df)
Eventually you will want to look at a subset of rows, using slicing. Looking up sorting… How do I find the rows with the highest or lowest values in a column you could use some