df.to_string(index=False, header=False)

这意味着，将 Dataframe 转换为字符串，但不包含索引标签和列（标题）标签。

我尝试这样做，我可以找到这个代码：

def print_df(df):
   # This code delete index and columns names
   df_ = df.copy()
   df_.columns = ['', '', '', '']
   df_.index = ['' for _ in range(len(df))]
   print(df_)

print_df(df)

其他方式，我发现，但没有正确的空格值之间的列格式：

[print(*row, sep=', ') for row in df.values.tolist()];

问：如何打印没有列的panda Dataframe

答：

print('\n'.join(df.to_string(index = False).split('\n')[1:]))

解释：

dfstr   = df.to_string(index = False) # Make str, possibly remove index
dfrows  = dfstr.split('\n')           # split on rows
dfprint = dfrows[1:]                  # Do not print row 0 (columns)
dfp     = '\n'.join(dfprint)          # Create a single string again

您可以在循环中使用print值，f-string s表示小数点后3位数，join：

for x in df.values:
    print (','.join(f'{y:.4f}' for y in x))

0.4444,0.0000,0.0000,0.0000,0.1111,0.0000,0.2222,0.0000,0.0000,0.0000
0.4444,0.3333,0.3333,0.4444,0.6667,1.0000,0.2222,0.1111,0.0000,0.0000
0.2222,0.0000,0.0000,0.0000,0.1111,0.1111,0.2222,0.0000,0.0000,0.0000

如果不需要换行符，则获取一行数据：

for x in df.values:
    print (','.join(f'{y:.4f}' for y in x), end='')

0.4444,0.0000,0.0000,0.0000,0.1111,0.0000,0.2222,0.0000,0.0000,0.00000.4444,0.3333,0.3333,0.4444,0.6667,1.0000,0.2222,0.1111,0.0000,0.00000.2222,0.0000,0.0000,0.0000,0.1111,0.1111,0.2222,0.0000,0.0000,0.0000