from pathlib import Path
from copy import copy
from typing import Union, Optional
import numpy as np
import pandas as pd
import openpyxl
from openpyxl import load_workbook
from openpyxl.utils import get_column_letter
def copy_excel_cell_range(
src_ws: openpyxl.worksheet.worksheet.Worksheet,
min_row: int = None,
max_row: int = None,
min_col: int = None,
max_col: int = None,
tgt_ws: openpyxl.worksheet.worksheet.Worksheet = None,
tgt_min_row: int = 1,
tgt_min_col: int = 1,
with_style: bool = True
) -> openpyxl.worksheet.worksheet.Worksheet:
"""
copies all cells from the source worksheet [src_ws] starting from [min_row] row
and [min_col] column up to [max_row] row and [max_col] column
to target worksheet [tgt_ws] starting from [tgt_min_row] row
and [tgt_min_col] column.
@param src_ws: source worksheet
@param min_row: smallest row index in the source worksheet (1-based index)
@param max_row: largest row index in the source worksheet (1-based index)
@param min_col: smallest column index in the source worksheet (1-based index)
@param max_col: largest column index in the source worksheet (1-based index)
@param tgt_ws: target worksheet.
If None, then the copy will be done to the same (source) worksheet.
@param tgt_min_row: target row index (1-based index)
@param tgt_min_col: target column index (1-based index)
@param with_style: whether to copy cell style. Default: True
@return: target worksheet object
"""
if tgt_ws is None:
tgt_ws = src_ws
# https://dev59.com/xWAg5IYBdhLWcg3wq8aU#34838233
for row in src_ws.iter_rows(min_row=min_row, max_row=max_row,
min_col=min_col, max_col=max_col):
for cell in row:
tgt_cell = tgt_ws.cell(
row=cell.row + tgt_min_row - 1,
column=cell.col_idx + tgt_min_col - 1,
value=cell.value
)
if with_style and cell.has_style:
# tgt_cell._style = copy(cell._style)
tgt_cell.font = copy(cell.font)
tgt_cell.border = copy(cell.border)
tgt_cell.fill = copy(cell.fill)
tgt_cell.number_format = copy(cell.number_format)
tgt_cell.protection = copy(cell.protection)
tgt_cell.alignment = copy(cell.alignment)
return tgt_ws
def append_df_to_excel(
filename: Union[str, Path],
df: pd.DataFrame,
sheet_name: str = 'Sheet1',
startrow: Optional[int] = None,
max_col_width: int = 30,
autofilter: bool = False,
fmt_int: str = "#,##0",
fmt_float: str = "#,##0.00",
fmt_date: str = "yyyy-mm-dd",
fmt_datetime: str = "yyyy-mm-dd hh:mm",
truncate_sheet: bool = False,
storage_options: Optional[dict] = None,
**to_excel_kwargs
) -> None:
"""
Append a DataFrame [df] to existing Excel file [filename]
into [sheet_name] Sheet.
If [filename] doesn't exist, then this function will create it.
@param filename: File path or existing ExcelWriter
(Example: '/path/to/file.xlsx')
@param df: DataFrame to save to workbook
@param sheet_name: Name of sheet which will contain DataFrame.
(default: 'Sheet1')
@param startrow: upper left cell row to dump data frame.
Per default (startrow=None) calculate the last row
in the existing DF and write to the next row...
@param max_col_width: maximum column width in Excel. Default: 40
@param autofilter: boolean - whether add Excel autofilter or not. Default: False
@param fmt_int: Excel format for integer numbers
@param fmt_float: Excel format for float numbers
@param fmt_date: Excel format for dates
@param fmt_datetime: Excel format for datetime's
@param truncate_sheet: truncate (remove and recreate) [sheet_name]
before writing DataFrame to Excel file
@param storage_options: dict, optional
Extra options that make sense for a particular storage connection, e.g. host, port,
username, password, etc., if using a URL that will be parsed by fsspec, e.g.,
starting “s3://”, “gcs://”.
@param to_excel_kwargs: arguments which will be passed to `DataFrame.to_excel()`
[can be a dictionary]
@return: None
Usage examples:
>>> append_df_to_excel('/tmp/test.xlsx', df, autofilter=True,
freeze_panes=(1,0))
>>> append_df_to_excel('/tmp/test.xlsx', df, header=None, index=False)
>>> append_df_to_excel('/tmp/test.xlsx', df, sheet_name='Sheet2',
index=False)
>>> append_df_to_excel('/tmp/test.xlsx', df, sheet_name='Sheet2',
index=False, startrow=25)
>>> append_df_to_excel('/tmp/test.xlsx', df, index=False,
fmt_datetime="dd.mm.yyyy hh:mm")
(c) [MaxU](https://stackoverflow.com/users/5741205/maxu?tab=profile)
"""
def set_column_format(ws, column_letter, fmt):
for cell in ws[column_letter]:
cell.number_format = fmt
filename = Path(filename)
file_exists = filename.is_file()
# process parameters
# calculate first column number
# if the DF will be written using `index=True`, then `first_col = 2`, else `first_col = 1`
first_col = int(to_excel_kwargs.get("index", True)) + 1
# ignore [engine] parameter if it was passed
if 'engine' in to_excel_kwargs:
to_excel_kwargs.pop('engine')
# save content of existing sheets
if file_exists:
wb = load_workbook(filename)
sheet_names = wb.sheetnames
sheet_exists = sheet_name in sheet_names
sheets = {ws.title: ws for ws in wb.worksheets}
with pd.ExcelWriter(
filename.with_suffix(".xlsx"),
engine="openpyxl",
mode="a" if file_exists else "w",
if_sheet_exists="new" if file_exists else None,
date_format=fmt_date,
datetime_format=fmt_datetime,
storage_options=storage_options
) as writer:
if file_exists:
# try to open an existing workbook
writer.book = wb
# get the last row in the existing Excel sheet
# if it was not specified explicitly
if startrow is None and sheet_name in writer.book.sheetnames:
startrow = writer.book[sheet_name].max_row
# truncate sheet
if truncate_sheet and sheet_name in writer.book.sheetnames:
# index of [sheet_name] sheet
idx = writer.book.sheetnames.index(sheet_name)
# remove [sheet_name]
writer.book.remove(writer.book.worksheets[idx])
# create an empty sheet [sheet_name] using old index
writer.book.create_sheet(sheet_name, idx)
# copy existing sheets
writer.sheets = sheets
else:
# file doesn't exist, we are creating a new one
startrow = 0
# write out the DataFrame to an ExcelWriter
df.to_excel(writer, sheet_name=sheet_name, **to_excel_kwargs)
worksheet = writer.sheets[sheet_name]
if autofilter:
worksheet.auto_filter.ref = worksheet.dimensions
for xl_col_no, dtyp in enumerate(df.dtypes, first_col):
col_no = xl_col_no - first_col
width = max(df.iloc[:, col_no].astype(str).str.len().max(),
len(df.columns[col_no]) + 6)
width = min(max_col_width, width)
column_letter = get_column_letter(xl_col_no)
worksheet.column_dimensions[column_letter].width = width
if np.issubdtype(dtyp, np.integer):
set_column_format(worksheet, column_letter, fmt_int)
if np.issubdtype(dtyp, np.floating):
set_column_format(worksheet, column_letter, fmt_float)
if file_exists and sheet_exists:
# move (append) rows from new worksheet to the `sheet_name` worksheet
wb = load_workbook(filename)
# retrieve generated worksheet name
new_sheet_name = set(wb.sheetnames) - set(sheet_names)
if new_sheet_name:
new_sheet_name = list(new_sheet_name)[0]
# copy rows written by `df.to_excel(...)` to
copy_excel_cell_range(
src_ws=wb[new_sheet_name],
tgt_ws=wb[sheet_name],
tgt_min_row=startrow + 1,
with_style=True
)
# remove new (generated by Pandas) worksheet
del wb[new_sheet_name]
wb.save(filename)
wb.close()
