Commit 0c660788 authored by LE GAC Renaud's avatar LE GAC Renaud
Browse files

Polish tool tip for report user interface.

parent 794ebdea
......@@ -88,23 +88,18 @@ TP_CONDITIONS = \
TP_GROUP_FIELD_LISTS = \
"Row are grouped according to the value of that field. " \
"It can be any field of the history table including those of " \
"the foreign tables, the individual property of the history.data " \
"dictionary, or 'year'."
"It can be any field defined in the source."
TP_GROUP_FIELD_METRICS = \
"Metric are computed for each value of that field. " \
"It can be any field of the history table including those of the " \
"foreign tables, the individual property of the history.data dictionary " \
"or 'year'"
"It can be any field defined in the source"
TP_FEATURES = "Summary value can be computed for columns."
TP_SORTERS = \
"Entries are sorted according to the value of these fields. "\
"It can be any field of the history table including those of the "\
"foreign tables, the individual property of the history.data dictionary, "\
"or 'year'. Descending order is obtained by using the '~field' construct."
"It can be any field defined in the source. "\
"Descending order is obtained by using the '~field' construct."
TP_SUMMARY_X = "To sum, for example, the content of each row."
TP_SUMMARY_Y = "To sum, for example, the content of each column."
......
......@@ -14,15 +14,17 @@ COLUMN_GUIDE = "All columns will be configured when the field is empty"
EVAL_GUIDE = """
It is possible to add new columns which are derived from existing ones using
arithmetical expressions. The expression is written in natural language
with one columns assignment per line. For more details have a look to the
function pandas.eval and to the method pandas.DataFrame.eval.
arithmetical expressions. Variables are column names while operator are:
+, -, /, *, in, not in, &, |, and, or, etc. One assignment per line.
For more details have a look to the function pandas.eval and to the
method pandas.DataFrame.eval.
"""
QUERY_GUIDE = """
It is possible to filter the source by applying a query on its fields.
The query is written in natural language using arithmetical expressions.
For more details have a look to the method pandas.DataFrame.query.
Variables are column names while operator are: +, -, /, *, in, not in,
&, |, and, or, etc. For more details have a look to the method
pandas.DataFrame.query.
"""
......
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