df["id"]=df["id"].round(2)
id列只保留两位小数
单独列还可以dtype=np.int64指定，多个列用dtype={"id":np.int64,"name":str}
df_y = pd.DataFrame(np.random.choice(2, batch_size), dtype=np.int64, columns=["y"])
如果是所有列：借助demicals保持高精度
value_a = np.around(np.random.normal(0, 1, (batch_size, col)), decimals=5, out=None)
某一列str转数字类型： pd.to_numeric(s)
>>> import pandas as pd
>>> s = pd.Series(['1.0', '2', -3])
>>> pd.to_numeric(s)
0 1.0
1 2.0
2 -3.0
dtype: float64
>>> pd.to_numeric(s, downcast='float')
0 1.0
1 2.0
2 -3.0
dtype: float32
>>> pd.to_numeric(s, downcast='signed')
0 1
1 2
2 -3
dtype: int8
>>> s = pd.Series(['apple', '1.0', '2', -3])
>>> pd.to_numeric(s, errors='ignore')
0 apple
1 1.0
2 2
3 -3
dtype: object
>>> pd.to_numeric(s, errors='coerce')
0 NaN
1 1.0
2 2.0
3 -3.0
dtype: float64
See also
--------
pandas.DataFrame.astype : Cast argument to a specified dtype.
pandas.to_datetime : Convert argument to datetime.
pandas.to_timedelta : Convert argument to timedelta.
numpy.ndarray.astype : Cast a numpy array to a specified type.