我想使用pandas.read_csv
1891, 91920, 7, 628,249, 59,51.0, 0.026, 0.028, NaN, NaN, NaN, NaN, NaN, 0.156, 0.071, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 21,500, 21,43.8, 0.005, 0.619, NaN,45.6, 0.048, 0.053, NaN, NaN, NaN, NaN, NaN, -0.180, 0.088, 20, 0.012, 1.107, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN
1891, 91920, 16, 628,135, 22,41.2, 0.093, 0.087, NaN, NaN, NaN, NaN, NaN, 0.416, 0.212, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 21,500, 20,23.3, 0.021, 2.023, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN
1891, 91920, 3, 628, 28, 39,47.0, 0.041, 0.044, NaN, NaN, NaN, NaN, NaN, -0.006, 0.064, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 21,500, 21,37.5, 0.009, 0.964, NaN,45.3, 0.054, 0.055, NaN, NaN, NaN, NaN, NaN, -0.838, 0.228, 20, 0.013, 1.193, NaN,51.8, 0.025, 0.026, NaN, NaN, NaN, NaN, NaN, -0.021, 0.054, 21, 0.005, 0.540, NaN, NaN, NaN, NaN
1891, 91920, 6, 628,276, 20,40.0, 0.118, 0.101, NaN, NaN, NaN, NaN, NaN, -0.767, 0.558, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 21,500, 20,26.7, 0.032, 2.982, NaN,41.0, 0.088, 0.089, NaN, NaN, NaN, NaN, NaN, -0.141, 0.233, 20, 0.024, 2.074, NaN,46.2, 0.053, 0.049, NaN, NaN, NaN, NaN, NaN, 0.080, 0.034, 21, 0.012, 1.187, NaN, NaN, NaN, NaN
我因为NaN值而尝试阅读它时遇到问题。如果文件是一个csv文件（昏迷分开）我没有问题，但它有空格。当我使用以下方式阅读时：
df = pd.read_csv(file,index_col=None, header=None)
显然，带有NaN的列被读作字符串，因为空格。如果空间具有相同的尺寸，我的问题很容易。我可以用：
df = pd.read_csv(file,index_col=None, header=None, na_values = " NaN")
并解决了问题，但是列中有不同的空格。其中一些在NaN之前有4个空格，其他6个等等。
所以，我的问题是：是否有正则表达式来指定像na_values这样的na_values = "\s+ NaN"？
答案 0 :(得分：0)
试试这个：
df = pd.read_csv(engine='python', index_col=None, sep=',\s*', header=None)
解析引擎设置为python，以避免在使用正则表达式作为分隔符时出现警告。