Pandas DataFrame导出到Excel导致TypeError
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。