def _fix_value_render(self, df, first_data_row, col_names, cols,
value_render_option):
"""Replace values for columns that need a different value render option."""
if not is_indexes(cols):
cols = find_col_indexes(cols, col_names)
for ix, col in enumerate(self._get_columns(cols, value_render_option)):
df.iloc[:, cols[ix] - 1] = rightpad(col[first_data_row:], len(df))
def df_to_sheet(
self,
df,
index=True,
headers=True,
start=(1, 1),
replace=False,
sheet=None,
raw_column_names=None,
raw_columns=None,
freeze_index=False,
freeze_headers=False,
fill_value="",
add_filter=False,
merge_headers=False,
flatten_headers_sep=None,
):
"""
Save a DataFrame into a worksheet.
Parameters
----------
df : DataFrame
the DataFrame to save
index : bool
whether to include the index in worksheet (default True)
headers : bool
whether to include the headers in the worksheet (default True)
start : tuple,str
tuple indicating (row, col) or string like 'A1' for top left
cell (default (1,1))
replace : bool
whether to remove everything in the sheet first (default False)
sheet : str,int,Worksheet
optional, if you want to open or create a different sheet
before saving,
see :meth:`open_sheet <gspread_pandas.spread.Spread.open_sheet>`
(default None)
raw_column_names : list, str
(DEPRECATED use raw_collumns instead) optional, list of columns
from your dataframe that you want interpreted as RAW input in
google sheets.
raw_columns : list, str
optional, list of columns from your dataframe that you want
interpreted as RAW input in google sheets. This can be column
names or column numbers.
freeze_index : bool
whether to freeze the index columns (default False)
freeze_headers : bool
whether to freeze the header rows (default False)
fill_value : str
value to fill nulls with (default '')
add_filter : bool
whether to add a filter to the uploaded sheet (default False)
merge_headers : bool
whether to merge cells in the header that have the same value
(default False)
flatten_headers_sep : str
if you want to flatten your multi-headers to a single row,
you can pass the string that you'd like to use to concatenate
the levels, for example, ': ' (default None)
Returns
-------
None
"""
self._ensure_sheet(sheet)
header = df.columns
index_size = df.index.nlevels if index else 0
header_size = df.columns.nlevels
if index:
df = df.reset_index()
df = fillna(df, fill_value)
df_list = df.values.tolist()
if headers:
header_rows = parse_df_col_names(df, index, index_size,
flatten_headers_sep)
df_list = header_rows + df_list
start = get_cell_as_tuple(start)
sheet_rows, sheet_cols = self.get_sheet_dims()
req_rows = len(df_list) + (start[ROW] - 1)
req_cols = len(df_list[0]) + (start[COL] - 1) or 1
end = (req_rows, req_cols)
if replace:
# this takes care of resizing
self.clear_sheet(req_rows, req_cols)
else:
# make sure sheet is large enough
self.sheet.resize(max(sheet_rows, req_rows),
max(sheet_cols, req_cols))
if raw_column_names:
deprecate(
"raw_column_names is deprecated, please use raw_columns instead."
)
raw_columns = find_col_indexes(raw_column_names, header,
start[COL] + index_size)
elif raw_columns:
if is_indexes(raw_columns):
offset = index_size + start[COL] - 1
raw_columns = [ix + offset for ix in raw_columns]
else:
raw_columns = find_col_indexes(raw_columns, header,
start[COL] + index_size)
self.update_cells(
start=start,
end=end,
vals=[str(val) for row in df_list for val in row],
raw_columns=raw_columns,
)
self.freeze(
None if not freeze_headers else header_size + start[ROW] - 1,
None if not freeze_index else index_size + start[COL] - 1,
)
if add_filter:
self.add_filter((header_size + start[ROW] - 2, start[COL] - 1),
(req_rows, req_cols))
if merge_headers:
self.spread.batch_update({
"requests":
create_merge_headers_request(self.sheet.id, header, start,
index_size)
})
self.refresh_spread_metadata()