. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... Dask Name: read-parquet, 1 graph layer Inspecting the ddf object, we see a few things • There are familiar attributes like .columns analysis toolkit, Release 1.4.4 Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 Name: read-parquet, 1 graph layer In [27]: ddf["name"] Out[27]: Dask Series Structure: npartitions=12 object ... ... ... ... Name: name, dtype: object Dask Name: getitem, 2 graph layers In [28]: ddf["name"]

. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... Dask Name: read-parquet, 1 graph layer Inspecting the ddf object, we see a few things • There are familiar attributes like .columns hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [38]: ddf Out[38]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 Name: read-parquet, 1 graph layer In [39]: ddf["name"] Out[39]: Dask Series Structure: npartitions=12 object ... ... ... ... Name: name, dtype: object Dask Name: getitem, 2 graph layers In [40]: ddf["name"]

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts toolkit, Release 1.0.0 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts toolkit, Release 1.0.5 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts toolkit, Release 1.0.3 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. 2.24. Scaling to large datasets 865 pandas: powerful Python data analysis toolkit, Release 1.2 Python data analysis toolkit, Release 1.2.3 of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that his feature requires version 0.12.0 or later of the pandas-gbq package

hasn’t actually read the data yet. Rather than executing immediately, doing operations build up a task graph. In [26]: ddf Out[26]: Dask DataFrame Structure: id name x y npartitions=12 int64 object float64 case a concrete pandas Series with the count of each name. Calling .compute causes the full task graph to be executed. This includes reading the data, selecting the columns, and doing the value_counts Jupyter notebook widget. 'tqdm_gui' Use the tqdm.tqdm_gui() function to display a progress bar as a graph- ical dialog box. Note that this feature requires version 0.12.0 or later of the pandas-gbq package