  Catalogs of the Zurich Observatory contain positional information on
sunspots, prominences and faculae in late 19th and early 20th centuries. This
database is given in handwritten tabular form and was not systematically
analysed earlier. It is different from the sunspot number time series made in
Zurich and was obtained with a larger telescope. We trained a neural-network
model for handwritten text recognition and present the database of
reconstructed coordinates. The database obtained connects the earlier
observations by Sp\"orer with later programs of the 20th century and
supplements the sunspot-group catalogs of the Royal Greenwich Observatory. We
also expect that the presented machine-learning approach and its deep
capabilities will motivate the processing of a wide bulk of astronomical data,
which is still given in non-digitized form or as plain scanned images.
