openpyxl：在某些（关键用途）情况下，公式被读作空白

Question

我的代码从googledrive（使用pydrive）下载一个.xlsx文件，找到一些带有pandas的空白单元格，并用openpyxl填充这些空白单元格。

当我打开openpyxl修改过的文件时，一切看起来都很好。但是，当我使用pandas read_excel函数时，所有包含公式的单元格都会被读取为空白。我怀疑问题出在openpyxl上，因为当我在驱动器上预览文件时，这些单元格是空白的。openpyxl没有触及的文件没有问题。

看起来我的问题与this one非常相似，但由于我的目标是不触及公式（我只想填充空白单元格），所以我不想解析公式，也不确定如何或是否应用Felipe's修复。

我希望能够下载该文件，用bokeh绘制它，用户和python都将编辑程序，所以我真的希望pandas能够阅读方程，无论是用户修改的文件还是openpyxl修改的文件。文件中的公式是点击并拖动“共享公式”，如果可能的话，我希望保持这种方式，因此理想情况下我希望避免使用data_only=True。我尝试指定data_only=False，但这似乎没有改变任何东西。

我使用的是openpyxl2.3.52.4，并且在代码运行时保持excel关闭。

openpyxl修改前后的文件版本是available here。

我的代码在这里，所有的openpyxl代码都被隔离到： #导入库 导入日期时间 进口杂质 导入操作系统 将熊猫作为pd导入 从openpyxl导入加载工作簿 从itertools import islice #bokeh互动的相对进口

dl = imp.load_source('downloader', os.getcwd() +
                      '/Project/downloader.py')
gdu = imp.load_source('googledriveutils', os.getcwd() +
                      '/Project/googledriveutils.py')
remove_file = gdu.remove_file
find_folderid = gdu.find_folderid
get_file_list = gdu.get_file_list


# Define constants
COL_LABEL = '\nProbe - '
# TODO: ORP PROBE: REVISE THIS DATE when orp probe is added
IGNORE_BEFORE = pd.to_datetime('5.24.2016')
PROBE_DICT = {'DO (mg/L)': 'DO mg/L',
              'pH': 'pH',
              'NH4+ (mgN/L)': 'Ammonium',
              'ORP (mV)': 'ORP mV'}
TS = '\nTimestamps'


def save_to_workbook(newval,
                     date,
                     header,
                     rows_to_skip=12,
                     wbname='temp.xlsx',
                     sheet_name='Reactor Data'):
    wb = load_workbook(wbname)
    ws = wb[sheet_name]
    for cell in ws[rows_to_skip+1]:
        # TODO: Error if header isn't found
        if cell.value == header:
            colno = cell.col_idx
            break

    for row in ws.iter_rows(min_row=rows_to_skip+1, min_col=1, max_col=1):
        for cell in row:
        # TODO: Error if date isn't found
            if cell.value == date:
                rowno = cell.row
                break

    ws.cell(row=rowno, column=colno).value = newval
    wb.save(wbname)


    return df





def find_r1masterfile():
    # Navigate through the directories
    wlab_fid = find_folderid('Winkler Lab', 'root')
    kp_fid = find_folderid('KathrynsProjects', wlab_fid)
    amxrct_fid = find_folderid('Anammox Reactor', kp_fid)
    trials_fid = find_folderid('Reactor Trials', amxrct_fid)
    # List files in directory
    file_list = get_file_list(trials_fid)
    for afile in file_list:
        if afile['title'] == 'AMX RCT.xlsx':
            # Return the file we asked for
                return afile
        # TODO: error if there was no file with that name


def save_r1masterfile(csv, rows_to_skip=12, filename='temp.xlsx', sheet_name='Reactor Data'):
    # Get the file we want
    master_file = find_r1masterfile()
    try:
        master_file.GetContentFile(filename)
    except Exception, e:
        print "Warning: Something wrong with file R1 Master File."
        print str(e)
        # TODO: add an email alarm to responsible user

    if csv:
        return master_file
    else:
        # convert to dataframe
        wb = load_workbook(filename, data_only=True)
        ws = wb[sheet_name]
        print ws["B14"].value
        data = ws.values
        data = list(data)[rows_to_skip:]
        cols = list(data[0])
        del cols[0]
        del data[0]
        idx = [r[0] for r in data]
        data = (islice(r, 1, None) for r in data)
        df = pd.DataFrame(data, index=idx, columns=cols)
        print df.dropna(how='all')
        remove_file(filename)
        return df


def upload_r1masterfile(filename='temp.xlsx'):
    # Get the file we want
    master_file = find_r1masterfile()
    try:
        master_file.SetContentFile(filename)
        master_file.Upload()
    except Exception, e:
        print "Warning: Something wrong with file R1 Master File."
        print str(e)
        # TODO: add an email alarm to responsible user


def populate_r1masterfile(rows_to_skip=12, filename='temp.xlsx'):
    # Get the R1 master file as a file
    save_r1masterfile(True)
    # Convert the juicy stuff to a dataframe
    masterdf = pd.read_excel(filename,
                             sheetname='Reactor Data',
                             encoding="utf-16",
                             skiprows=rows_to_skip,
                             sep='\t',
                             index_col='Date',
                             keep_default_na=False,
                             na_values=['-1.#IND', '1.#QNAN', '1.#IND',
                             '-1.#QNAN', '','N/A', '#NA', 'NA'
                             'NULL', 'NaN', '-NaN', 'nan', '-nan'])
    # Find what we will populate with probe data
    # Find timestamps
    ts_columns = [col for col in masterdf.columns if TS in col]
    tsdf = masterdf[ts_columns]
    # Find probes, ignore before given date
    probe_columns = [col for col in masterdf.columns if COL_LABEL in col]
    probedf = masterdf[probe_columns]
    probedf = probedf[masterdf.index > IGNORE_BEFORE]
    # Find Indices and column labels of blank values
    stackdf = probedf.stack(dropna=False)
    empty = stackdf[stackdf.isnull()].index.tolist()

    # For each blank look for the probe, time & date of cycle, and return val
    for each in empty:
        probe, time = each[1].split(COL_LABEL)
        time = tsdf.loc[each[0], time+TS]
        ts = each[0]+pd.DateOffset(hour=time.hour, minute=time.minute)
        val = dl.get_val_from(1, ts, PROBE_DICT.get(probe))
        probedf.set_value(each[0], each[1], val)
        # Save that value to the workbook
        save_to_workbook(val, each[0], each[1])
    upload_r1masterfile()
    print 'Master file updated. ' + str(datetime.datetime.now())
    remove_file('temp.xlsx')
    return probedf

更新

我根据Charlie的建议修改了我的代码（上面更新了）。但数据框里还是没有。为了提供一个更具体的示例，我运行此代码时为什么会这样：

^{pr2}$

用this file，我回来了？公司名称：

Value of B14 Formula is: None

有解决办法吗？

Answer 1

查理的回答来自mailing list：

So, if you want to keep the formulae then you must not use data only mode.
As previously stated, openpyxl never evaluates formulae so if you want to
know value of A3 you must pass the file to an application such as Excel
or OpenOffice — you can run OpenOffice headless for this kind of thing or
use xlwings for Excel — that does do formula evaluation. You could then
read this file in data only mode to see the result of the calculation.
Alternatively you could try using something like PyCel to do the
evaluation for you. But, basically if you want to do calculations: do them
in Python.

根据他的建议，我的解决办法是按excel文件中的方法逐列重做所有的计算。一、 E.对于这样的excel文件：

        col1 col2   col3    col4
row1    1    3      =A1+B1  =1+3
row2    2    4      =A2+B2  =2+4

我将其作为数据帧导入，如下所示（以字符串形式维护方程）：

^{pr2}$

然后执行以下操作：

parse_excel = lambda x: eval(str(x)[1:]) if isinstance(x, str) else x
for col in df.columns:
    try:
        df[col] = df[col].map(parse_excel)
    except:
        pass
df['col3'] = df['col2']+df['col1']

我敢肯定这也许是最笨拙的方法，但它目前有效。在