/Users/imac/anaconda3/envs/pythonProject/bin/python /Users/imac/PycharmProjects/pythonProject/合并.py Traceback (most recent call last): File "/Users/imac/PycharmProjects/pythonProject/合并.py", line 6, in <module> merged = pd.merge(file1, file2, on='staxids_X', how='left') File "/Users/imac/anaconda3/envs/pythonProject/lib/python3.10/site-packages/pandas/core/reshape/merge.py", line 142, in merge op = _MergeOperation( File "/Users/imac/anaconda3/envs/pythonProject/lib/python3.10/site-packages/pandas/core/reshape/merge.py", line 735, in __init__ self._maybe_coerce_merge_keys() File "/Users/imac/anaconda3/envs/pythonProject/lib/python3.10/site-packages/pandas/core/reshape/merge.py", line 1387, in _maybe_coerce_merge_keys raise ValueError(msg) ValueError: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat Process finished with exit code 1这是报错吗

是的，这个错误的原因是您尝试将一个 object 类型的列和一个 int64型的列进行合并，不支持这种数据类型的合并。

解决方法有两种：

1. 确认要进行合并的列的数据类型是否一致，如果不一致，将其转换为相同的数据类型再进行合并。

2. 如果您希望在合并时保留所有的行，可以使用 pd.concat() 方法进行连接，而不是使用 pd.merge() 方法进行合并。具体步骤如下：

import pandas as pd

file1 = pd.read_csv('file1.csv')
file2 = pd.read_csv('file2.csv')

merged = pd.concat([file1, file2], ignore_index=True)
merged.to_csv('merged.csv', index=False)

其中，ignore_index=True 表示重新生成行索引。

希望这些信息对您有所帮助！