要将pandas DataFrame写入CSV文件，您需要DataFrame.to_csv。此函数提供了许多具有合理默认值的参数，您通常需要重写这些参数以适应特定的用例。例如，您可能希望使用不同的分隔符、更改datetime格式或在写入时删除索引。To_csv具有参数，您可以传递这些参数来满足这些需求。

下面的表格列出了写入CSV文件的一些常见场景，以及您可以为它们使用的相应参数。

Footnotes The default separator is assumed to be a comma (','). Don't change this unless you know you need to. By default, the index of df is written as the first column. If your DataFrame does not have an index (IOW, the df.index is the default RangeIndex), then you will want to set index=False when writing. To explain this in a different way, if your data DOES have an index, you can (and should) use index=True or just leave it out completely (as the default is True). It would be wise to set this parameter if you are writing string data so that other applications know how to read your data. This will also avoid any potential UnicodeEncodeErrors you might encounter while saving. Compression is recommended if you are writing large DataFrames (>100K rows) to disk as it will result in much smaller output files. OTOH, it will mean the write time will increase (and consequently, the read time since the file will need to be decompressed).

它可能不是这种情况下的答案，但因为我有相同的错误消息与.to_csv尝试.toCSV('name.csv')和错误消息是不同的("SparseDataFrame'对象没有属性'toCSV')。因此，通过将数据帧转换为密集数据帧解决了这个问题

df.to_dense().to_csv("submission.csv", index = False, sep=',', encoding='utf-8')

当您使用to_csv方法将DataFrame对象存储到csv文件中时，您可能不需要存储DataFrame对象的每一行的前面索引。

你可以通过给索引参数传递一个False布尔值来避免这种情况。

有点像:

df.to_csv(file_name, encoding='utf-8', index=False)

如果你的DataFrame对象是这样的:

  Color  Number
0   red     22
1  blue     10

csv文件将存储:

Color,Number
red,22
blue,10

而不是(当传递默认值True时的情况)

,Color,Number
0,red,22
1,blue,10

我会避免使用“\t”分隔符，这会在再次读取数据集时产生问题。

df。to_csv (file_name、编码=“utf - 8”)

要将pandas DataFrame写入CSV文件，您需要DataFrame.to_csv。此函数提供了许多具有合理默认值的参数，您通常需要重写这些参数以适应特定的用例。例如，您可能希望使用不同的分隔符、更改datetime格式或在写入时删除索引。To_csv具有参数，您可以传递这些参数来满足这些需求。

下面的表格列出了写入CSV文件的一些常见场景，以及您可以为它们使用的相应参数。

Footnotes The default separator is assumed to be a comma (','). Don't change this unless you know you need to. By default, the index of df is written as the first column. If your DataFrame does not have an index (IOW, the df.index is the default RangeIndex), then you will want to set index=False when writing. To explain this in a different way, if your data DOES have an index, you can (and should) use index=True or just leave it out completely (as the default is True). It would be wise to set this parameter if you are writing string data so that other applications know how to read your data. This will also avoid any potential UnicodeEncodeErrors you might encounter while saving. Compression is recommended if you are writing large DataFrames (>100K rows) to disk as it will result in much smaller output files. OTOH, it will mean the write time will increase (and consequently, the read time since the file will need to be decompressed).

在Windows上导出全路径文件的例子，如果你的文件有头文件:

df.to_csv (r'C:\Users\John\Desktop\export_dataframe.csv', index = None, header=True) 

例如，如果你想将文件存储在脚本所在的目录中，使用utf-8编码和制表符作为分隔符:

df.to_csv(r'./export/dftocsv.csv', sep='\t', encoding='utf-8', header='true')