def _table_header(rd):
count = 1
rc = th()
for i in rd:
rc += th(_header_entry(count % 2, i), _class="skew")
count += 1
return thead(tr(HTML(str(rc))))
def _table_header(rd):
count = 1
rc = th()
for i in rd:
rc += th(_header_entry(count % 2, i), _class="skew")
count += 1
return thead(tr(HTML(str(rc))))
def frequency_table(item_counts, name, max_items=10):
""" create a table of item frequencies """
# create header
row = htmltag.tr(htmltag.th(name), htmltag.th('Count'))
thead = htmltag.thead(row)
# add items
trs = []
items = [(v, k) for (k, v) in item_counts.items()]
items.sort(reverse=True)
if len(items) > max_items:
items = items[:max_items]
for (value, key) in items:
row = htmltag.tr(htmltag.td(key), htmltag.td(str(value)))
trs.append(row)
tbody = htmltag.tbody(*trs)
return htmltag.table(thead, tbody)
def frequency_table(item_counts, name, sort=True, max_items=10):
""" create a table of item frequencies """
# create header
tr = htmltag.tr(htmltag.th(name), htmltag.th('Count'))
thead = htmltag.thead(tr)
# add items
trs = []
items = [(v, k) for (k, v) in item_counts.items()]
items.sort(reverse=True)
if len(items) > max_items:
items = items[:max_items]
for (value, key) in items:
tr = htmltag.tr(htmltag.td(key), htmltag.td(str(value)))
trs.append(tr)
tbody = htmltag.tbody(*trs)
return htmltag.table(thead, tbody)
def table(df, sortable=False, last_row_is_footer=False, col_format=None):
""" generate an HTML table from a pandas data frame
Args:
df (df): pandas DataFrame
col_format (dict): format the column name (key)
using the format string (value)
Returns:
HTML (str)
"""
if col_format is None:
col_format = {}
row_count = len(df)
# default column formatting
default_format = {
'align': 'right',
'decimal_places': 2,
'commas': True,
'width': None,
}
def get_format(col, attribute):
""" helper function to get column formatting
Args:
col: column name (key in the col_format)
attribute (str)
Returns:
format (str) for the specified col
"""
if col in col_format and attribute in col_format[col_name]:
value = col_format[col_name][attribute]
elif '*' in col_format and attribute in col_format['*']:
value = col_format['*'][attribute]
else:
value = default_format[attribute]
return value
# create header
items = []
# if there's a hierarchical index for the columns, span the top level; only suppots 2 levels
if isinstance(df.columns[0], tuple):
headers = []
prev_header = df.columns[0][0]
span = 0
for i, col_name in enumerate(df.columns):
h1 = col_name[0]
h2 = col_name[1]
if h1 == prev_header:
span += 1
if i == (len(df.columns)-1):
headers.append(htmltag.th(h1, colspan=span, _class='centered'))
else:
headers.append(htmltag.th(prev_header, colspan=span, _class='centered'))
if i == (len(df.columns)-1):
headers.append(htmltag.th(h1, colspan=1))
else:
prev_header = h1
span = 1
if get_format(col_name, 'align') == 'right':
items.append(htmltag.th(h2, _class='alignRight'))
else:
items.append(htmltag.th(h2))
thead = htmltag.thead(htmltag.tr(*headers), htmltag.tr(*items))
else:
for col_name in df.columns:
if get_format(col_name, 'align') == 'right':
if sortable:
items.append(htmltag.th(col_name, **{'class':'alignRight', 'data-sortable':'true'}))
else:
items.append(htmltag.th(col_name, _class='alignRight'))
else:
if sortable:
items.append(htmltag.th(col_name, **{'data-sortable':'true'}))
else:
items.append(htmltag.th(col_name))
thead = htmltag.thead(htmltag.tr(*items))
# create body (and optionally footer)
tfoot = ''
rows = []
for i, row in df.iterrows():
values = row.tolist()
items = []
for j, v in enumerate(values):
col_name = df.columns[j]
if is_numeric(v):
decimal_places = get_format(col_name, 'decimal_places')
if get_format(col_name, 'commas'):
pattern = '{:,.' + str(decimal_places) + 'f}'
else:
pattern = '{:.' + str(decimal_places) + 'f}'
v = pattern.format(v)
if get_format(col_name, 'align') == 'right':
items.append(htmltag.td(v, _class='alignRight'))
# TODO - need to implement width control
#width = get_format(col_name, 'width')
#if is_numeric(width):
# style='width:' + str(width) + 'px'
# items.append(htmltag.td(v, style=style ))
else:
items.append(htmltag.td(v))
if last_row_is_footer and i == row_count - 1:
tfoot = htmltag.tfoot(htmltag.tr(*items))
else:
rows.append(htmltag.tr(*items))
tbody = htmltag.tbody(*rows)
# if sortable, apply the bootstrap-table tab, bs-table
if sortable:
if row_count > 15:
return htmltag.table(thead, tbody, tfoot, **{'class':'bs-table', 'data-striped':'true', 'data-height':'600'})
else:
return htmltag.table(thead, tbody, tfoot, **{'class':'bs-table', 'data-striped':'true'})
else:
return htmltag.table(thead, tbody, tfoot, **{'class':'table-striped'})
def table(df, sortable=False, last_row_is_footer=False, format=None):
""" generate an HTML table from a pandas data frame """
if not format:
format = {}
rowCount = len(df)
# default column formatting
default_format = {
'align': 'right',
'decimal_places': 2,
'commas': True,
'width': None,
}
# a helper function to get column formatting
def get_format(col_name, attribute):
if col_name in format and attribute in format[col_name]:
value = format[col_name][attribute]
elif '*' in format and attribute in format['*']:
value = format['*'][attribute]
else:
value = default_format[attribute]
return value
# create header
items = []
if isinstance(df.columns[0], tuple):
headers = []
prev_header = df.columns[0][0]
span = 0
for i, col_name in enumerate(df.columns):
h1 = col_name[0]
h2 = col_name[1]
if h1 == prev_header:
span += 1
if i == (len(df.columns) - 1):
headers.append(
htmltag.th(h1, colspan=span, _class='centered'))
else:
headers.append(
htmltag.th(prev_header, colspan=span, _class='centered'))
if i == (len(df.columns) - 1):
headers.append(htmltag.th(h1, colspan=1))
else:
prev_header = h1
span = 1
if get_format(col_name, 'align') == 'right':
items.append(htmltag.th(h2, _class='alignRight'))
else:
items.append(htmltag.th(h2))
thead = htmltag.thead(htmltag.tr(*headers), htmltag.tr(*items))
else:
for col_name in df.columns:
if get_format(col_name, 'align') == 'right':
if sortable:
items.append(
htmltag.th(
col_name, **{
'class': 'alignRight',
'data-sortable': 'true'
}))
else:
items.append(htmltag.th(col_name, _class='alignRight'))
else:
if sortable:
items.append(
htmltag.th(col_name, **{'data-sortable': 'true'}))
else:
items.append(htmltag.th(col_name))
thead = htmltag.thead(htmltag.tr(*items))
# create body (and optionally footer)
tfoot = ''
rows = []
for i, row in df.iterrows():
values = row.tolist()
if False: #
tf = t.tfoot
tr = tf.tr
items = []
for j, v in enumerate(values):
col_name = df.columns[j]
if is_numeric(v):
decimal_places = get_format(col_name, 'decimal_places')
if get_format(col_name, 'commas'):
pattern = '{:,.' + str(decimal_places) + 'f}'
else:
pattern = '{:.' + str(decimal_places) + 'f}'
v = pattern.format(v)
if get_format(col_name, 'align') == 'right':
items.append(htmltag.td(v, _class='alignRight'))
#width = get_format(col_name, 'width')
#if is_numeric(width):
# style='width:' + str(width) + 'px'
# items.append(htmltag.td(v, style=style ))
else:
items.append(htmltag.td(v))
if last_row_is_footer and i == rowCount - 1:
tfoot = htmltag.tfoot(htmltag.tr(*items))
else:
rows.append(htmltag.tr(*items))
tbody = htmltag.tbody(*rows)
if sortable:
if rowCount > 15:
return htmltag.table(
thead, tbody, tfoot, **{
'class': 'bs-table',
'data-striped': 'true',
'data-height': '600'
})
else:
return htmltag.table(
thead, tbody, tfoot, **{
'class': 'bs-table',
'data-striped': 'true'
})
else:
return htmltag.table(thead, tbody, tfoot, **{'class': 'table-striped'})