Pandas DataFrame导出到Excel导致TypeError

2 投票
1 回答
1169 浏览
提问于 2025-04-18 14:39

我正在尝试把一个pandas的数据框导出到Excel,方法是:

writer = pd.io.excel.ExcelWriter(args.out_file, engine='xlsxwriter', options={'constant_memory': True})
summary_data.to_excel(writer, sheet_name='summary', na_rep='NA', index=False)

但是我收到了这个信息:

"cannot convert the series to {0}".format(str(converter)))
TypeError: cannot convert the series to <type 'float'>

我的数据框没有问题,所以我对这个错误信息有点困惑。当数据框的行数少于1000时,这个错误不会出现,但一旦行数超过1000,就会出现这个错误。

有没有什么想法?

谢谢

更新 summary_data.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 2176 entries, 0 to 2175
Data columns (total 27 columns):
chrom                                   2176 non-null object
coord                                   2176 non-null int64
ref_base                                2176 non-null object
var_base                                2176 non-null object
normal_ref_counts                       2176 non-null int64
normal_var_counts                       2176 non-null int64
VOA867-A1_S43_merged_ref_counts         2176 non-null object
VOA867-A1_S43_merged_var_counts         2176 non-null object
VOA867-A1_S43_merged_somatic_status     2176 non-null object
VOA867-E02_S73_merged_ref_counts        2176 non-null object
VOA867-E02_S73_merged_var_counts        2176 non-null object
VOA867-E02_S73_merged_somatic_status    2176 non-null object
VOA867-F03_S76_merged_ref_counts        2176 non-null object
VOA867-F03_S76_merged_var_counts        2176 non-null object
VOA867-F03_S76_merged_somatic_status    2176 non-null object
VOA867-F04_S75_merged_ref_counts        2176 non-null object
VOA867-F04_S75_merged_var_counts        2176 non-null object
VOA867-F04_S75_merged_somatic_status    2176 non-null object
VOA867-F09_S74_merged_ref_counts        2176 non-null object
VOA867-F09_S74_merged_var_counts        2176 non-null object
VOA867-F09_S74_merged_somatic_status    2176 non-null object
VOA867-T_S41_merged_ref_counts          2176 non-null object
VOA867-T_S41_merged_var_counts          2176 non-null object
VOA867-T_S41_merged_somatic_status      2176 non-null object
VOA867xeno_S18_merged_ref_counts        2176 non-null object
VOA867xeno_S18_merged_var_counts        2176 non-null object
VOA867xeno_S18_merged_somatic_status    2176 non-null object
dtypes: int64(3), object(24)None

这是生成它的函数:

def get_summary_data(data, normal_sample):
    summary_data = []
    for index, normal_row in data[normal_sample].iterrows():
        out_row = {'chrom': index[0],
                   'coord': index[1],
                   'ref_base': normal_row['ref_base'],
                   'var_base': normal_row['var_base'],
                   'normal_ref_counts': normal_row['ref_counts'],
                   'normal_var_counts': normal_row['var_counts'],
                   }

        normal_variant_status = normal_row['variant_status']

        normal_depth = out_row['normal_ref_counts'] + out_row['normal_var_counts']

        if normal_depth > 0:
            normal_var_freq = out_row['normal_var_counts'] / normal_depth
        else:
            normal_var_freq = 0

        for sample in data:
            if sample == normal_sample:
                 continue

            sample_row = data[sample].ix[[index]]

            out_row['{0}_ref_counts'.format(sample)] = sample_row['ref_counts']

            out_row['{0}_var_counts'.format(sample)] = sample_row['var_counts']

            sample_variant_status = str(sample_row['variant_status'].iget(0))

            sample_somatic_status = call_somatic_status(normal_variant_status,
                                                        sample_variant_status,
                                                        normal_var_freq,
                                                        args.min_normal_germline_var_freq)

            out_row['{0}_somatic_status'.format(sample)] = sample_somatic_status

        summary_data.append(out_row)

    columns = ['chrom', 'coord', 'ref_base', 'var_base', 'normal_ref_counts', 'normal_var_counts']

    for sample in data:
        if sample == normal_sample:
            continue

        columns.append('{0}_ref_counts'.format(sample))

        columns.append('{0}_var_counts'.format(sample))

        columns.append('{0}_somatic_status'.format(sample))

    summary_data = pd.DataFrame(summary_data, columns=columns)

    return summary_data

count应该是整数,但我发现它在这里被当作字符串,可能是因为它是从另一个数据框提取出来的?

1 个回答

0

.to_excel 这个功能只接受类型为对象的列。快速解决这个问题的方法是,在写入之前把所有列都强制转换为对象类型,方法是:

summary_data = summary_data.astype(object)

这样你就可以顺利写入,而不会出错:

summary_data.to_excel(writer, sheet_name='summary', na_rep='NA', index=False)

这里有一些处理的步骤,因为在某些情况下,我需要把列复制成对象类型。真奇怪。另一种选择就是直接删除那些有问题的列。

撰写回答