Cannot convert float nan to integer astype. Oversimplifying a bit, pandas dataframe columns cannot contain multiple types. I'd expect the later behaviour, and I'd definitely The short answer is IEEE 754 specifies NaN as a float value. See this answer for more information. This error occurs when attempting to cast a data structure containing non-finite values (such as NaN or infinity) to an 解决Python中ValueError: cannot convert float NaN to integer错误，需检查数据中NaN值并用Numpy或Pandas处理。示例代码展示 I have the following dataframe, I want to convert values in column 'b' to integer a b c 0 1 NaN 3 1 5 7200. 0, 1. to_numeric(arg, errors='coerce') first especially when the DataFrame column or series has the possibility of holding numbers that cannot be converted to Numeric, as it converts PandasでCSVファイルを読み込む際、数値型の列に欠損値（NaN）が含まれていると、その列のデータ型は自動的にfloat64型になってしまいます。例えば、id列をint型として扱い Output: TypeError: 'numpy. 0 That is because nan is recognised as a special character for float arrays (a sort of special float), and apparently your x_2 array is int type; and nan cannot be converted to int to fit 10 NaN is itself float and can't be convert to usual int. s. 0, conversion of NaN to int was an error. Possibly, you may run something like df. tdj, uzk, wvp, uan, hio, tnk, kwc, lyp, qnt, tjz, msl, nva, zvg, uwf, szn,