def test_render_html_table(self):
assert (html_table([[
1, 2
]]).__html__() == '<table><tr><td>1</td><td>2</td></tr></table>')
assert (html_table([[1, 2]], columns=[
'a', 'b'
]).__html__() == '<table><thead><tr><th>a</th><th>b</th></tr></thead>'
'<tbody><tr><td>1</td><td>2</td></tr></tbody></table>')
def render_dataframe(df,
index=False,
*,
datatable=False,
class_=(),
col_display=None,
**kwargs):
"""
Convert a Pandas dataframe to a hyperpython structure.
Args:
df (DataFrame):
Input data frame.
col_display (map):
An optional mapping from column names in a dataframe to their
corresponding human friendly counterparts.
datatable (bool):
If True, prepare data to be handled by the Data table js library.
Additional attributes (such as class, id, etc) can be passed as keyword
arguments.
"""
if datatable:
class_ = [*class_, 'display', 'cell-border', 'compact']
data = np.array(df.astype(object))
columns = df.columns
if index:
data = np.hstack([df.index[:, None], df])
columns = [df.index.name or '', *columns]
columns = as_display_values(columns, col_display)
return html_table(data, columns=columns, class_=class_, **kwargs)
def render_dataframe(df, index=False, *, col_display=None, **kwargs):
"""
Convert a Pandas dataframe to a hyperpython structure.
Args:
df (DataFrame):
Input data frame.
col_display (map):
An optional mapping from column names in a dataframe to their
corresponding human friendly counterparts.
index (bool):
If given, add index as the first column.
Additional attributes (such as class, id, etc) can be passed as keyword
arguments.
"""
data = np.array(df.astype(object))
columns = df.columns
if index:
data = np.hstack([df.index[:, None], df])
columns = [df.index.name or "index", *columns]
if col_display:
columns = [col_display.get(x, x) for x in columns]
return html_table(data, columns=columns, style="width: 100%", **kwargs)
def votes_table(comments):
if comments:
data = [
[i, comment, vote_options(comment)]
for i, comment in enumerate(comments, 1)
]
return html_table(data, columns=['', _('Comment'), _('Options')], class_='table')
else:
return None
def cluster_info(cluster):
stereotypes = cluster.stereotypes.all()
user_data = [(user.username, user.name) for user in cluster.users.all()]
return {
'size':
cluster.users.count(),
'stereotypes':
stereotypes,
'stereotype_links': [
a(str(stereotype),
href=reverse('cluster:stereotype-vote',
kwargs={
'conversation': cluster.conversation,
'stereotype': stereotype,
})) for stereotype in stereotypes
],
'users':
html_table(user_data, columns=[_('Username'), _('Name')])
}
def map_to_html_table(cols):
array = map_to_table(cols)
cols, body = array
cols = [__(col) for col in cols]
return html_table([body], columns=cols, class_='ReportTable table')
def map_to_table(data):
array = np.array(list(data.items())).T
cols, body = array
return html_table([body], columns=[__(col) for col in cols], class_='ReportTable')