Comment écrire dans un fichier excel existant sans écraser des données (en utilisant pandas)?

avec openpyxl version 2.4.0 et pandas version 0.19.2 , le processus @ski est venu avec devient un peu plus simple:

import pandas
from openpyxl import load_workbook

with pandas.ExcelWriter('Masterfile.xlsx', engine='openpyxl') as writer:
    writer.book = load_workbook('Masterfile.xlsx')
    data_filtered.to_excel(writer, "Main", cols=['Diff1', 'Diff2'])
#That's it!

Voici une fonction d'aide:

def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None,
                       truncate_sheet=False, 
                       **to_excel_kwargs):
    """
    Append a DataFrame [df] to existing Excel file [filename]
    into [sheet_name] Sheet.
    If [filename] doesn't exist, then this function will create it.

    Parameters:
      filename : File path or existing ExcelWriter
                 (Example: '/path/to/file.xlsx')
      df : dataframe to save to workbook
      sheet_name : Name of sheet which will contain DataFrame.
                   (default: 'Sheet1')
      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...
      truncate_sheet : truncate (remove and recreate) [sheet_name]
                       before writing DataFrame to Excel file
      to_excel_kwargs : arguments which will be passed to `DataFrame.to_excel()`
                        [can be dictionary]

    Returns: None
    """
    from openpyxl import load_workbook

    # ignore [engine] parameter if it was passed
    if 'engine' in to_excel_kwargs:
        to_excel_kwargs.pop('engine')

    writer = pd.ExcelWriter(filename, engine='openpyxl')

    # Python 2.x: define [FileNotFoundError] exception if it doesn't exist 
    try:
        FileNotFoundError
    except NameError:
        FileNotFoundError = IOError


    try:
        # try to open an existing workbook
        writer.book = load_workbook(filename)

        # 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 = {ws.title:ws for ws in writer.book.worksheets}
    except FileNotFoundError:
        # file does not exist yet, we will create it
        pass

    if startrow is None:
        startrow = 0

    # write out the new sheet
    df.to_excel(writer, sheet_name, startrow=startrow, **to_excel_kwargs)

    # save the workbook
    writer.save()

NOTE: pour les Pandas < 0.21.0, remplacer sheet_name par sheetname !

exemples d'utilisation:

append_df_to_excel('d:/temp/test.xlsx', df)

append_df_to_excel('d:/temp/test.xlsx', df, header=None, index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False)

append_df_to_excel('d:/temp/test.xlsx', df, sheet_name='Sheet2', index=False, startrow=25)

vieille question, mais je devine que certaines personnes cherchent encore ceci - ainsi...

je trouve cette méthode agréable parce que toutes les feuilles de travail sont chargées dans un dictionnaire de noms de feuilles et de paires de bases de données, créé par pandas avec l'option sheetname=None. Il est simple d'ajouter, de supprimer ou de modifier des feuilles de travail entre la lecture de la feuille de calcul dans le format dict et l'écriture à partir de la dict. Pour moi, le xlsxwriter fonctionne mieux que openpyxl pour cette tâche en termes de vitesse et de format.

Note: les versions futures de pandas (0.21.0+) changeront le paramètre "sheetname" en "sheet_name".

# read a single or multi-sheet excel file
# (returns dict of sheetname(s), dataframe(s))
ws_dict = pd.read_excel(excel_file_path,
                        sheetname=None)

# all worksheets are accessible as dataframes.

# easy to change a worksheet as a dataframe:
mod_df = ws_dict['existing_worksheet']

# do work on mod_df...then reassign
ws_dict['existing_worksheet'] = mod_df

# add a dataframe to the workbook as a new worksheet with
# ws name, df as dict key, value:
ws_dict['new_worksheet'] = some_other_dataframe

# when done, write dictionary back to excel...
# xlsxwriter honors datetime and date formats
# (only included as example)...
with pd.ExcelWriter(excel_file_path,
                    engine='xlsxwriter',
                    datetime_format='yyyy-mm-dd',
                    date_format='yyyy-mm-dd') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

pour l'exemple de la question de 2013:

ws_dict = pd.read_excel('Masterfile.xlsx',
                        sheetname=None)

ws_dict['Main'] = data_filtered[['Diff1', 'Diff2']]

with pd.ExcelWriter('Masterfile.xlsx',
                    engine='xlsxwriter') as writer:

    for ws_name, df_sheet in ws_dict.items():
        df_sheet.to_excel(writer, sheet_name=ws_name)

je sais que c'est un fil plus ancien, mais c'est le premier élément que vous trouvez lors de la recherche, et les solutions ci-dessus ne fonctionnent pas si vous avez besoin de conserver des graphiques dans un classeur que vous avez déjà créé. Dans ce cas, xlwings est une meilleure option - il vous permet d'écrire dans le livre excel et conserve les données graphiques.

exemple simple:

import xlwings as xw
import pandas as pd

#create DF
months = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
value1 = [x * 5+5 for x in range(len(months))]
df = pd.DataFrame(value1, index = months, columns = ['value1'])
df['value2'] = df['value1']+5
df['value3'] = df['value2']+5

#load workbook that has a chart in it
wb = xw.Book('C:\data\bookwithChart.xlsx')

ws = wb.sheets['chartData']

ws.range('A1').options(index=False).value = df

wb = xw.Book('C:\data\bookwithChart_updated.xlsx')

xw.apps[0].quit()

def append_sheet_to_master(self, master_file_path, current_file_path, sheet_name):
    try:
        master_book = load_workbook(master_file_path)
        master_writer = pandas.ExcelWriter(master_file_path, engine='openpyxl')
        master_writer.book = master_book
        master_writer.sheets = dict((ws.title, ws) for ws in master_book.worksheets)
        current_frames = pandas.ExcelFile(current_file_path).parse(pandas.ExcelFile(current_file_path).sheet_names[0],
                                                               header=None,
                                                               index_col=None)
        current_frames.to_excel(master_writer, sheet_name, index=None, header=False)

        master_writer.save()
    except Exception as e:
        raise e

cela fonctionne parfaitement bien seule chose est que le formatage du fichier maître(fichier auquel nous ajoutons une nouvelle feuille) est perdu.

writer = pd.ExcelWriter('prueba1.xlsx'engine='openpyxl',keep_date_col=True)

Le "keep_date_col" l'espoir de vous aider à