用定义的dtypes初始化pandas DataFrame

Question

该pd.DataFrame文档字符串指定为整个数据框标量参数:

dtype : dtype, default None Data type to force, otherwise infer

看起来它确实是一个标量,因为以下会导致错误:

dfbinseq = pd.DataFrame([],
                        columns = ["chr", "centre", "seq_binary"],
                        dtype = ["O", pd.np.int64, "O"])

dfbinseq = pd.DataFrame([],
                        columns = ["chr", "centre", "seq_binary"],
                        dtype = [pd.np.object, pd.np.int64, pd.np.object])

创建一个空数据框(我需要将其放入HDF5商店以供进一步使用append)的唯一解决方法是

dfbinseq.centre.dtype = np.int64

有没有办法dtypes立刻设置参数？

Answer 1

您可以设置dtype为Series:

import pandas as pd

df = pd.DataFrame({'A':pd.Series([], dtype='str'),
                   'B':pd.Series([], dtype='int'),
                   'C':pd.Series([], dtype='float')})

print (df)
Empty DataFrame
Columns: [A, B, C]
Index: []

print (df.dtypes)
A     object
B      int32
C    float64
dtype: object

有了数据:

df = pd.DataFrame({'A':pd.Series([1,2,3], dtype='str'),
                   'B':pd.Series([4,5,6], dtype='int'),
                   'C':pd.Series([7,8,9], dtype='float')})

print (df)
   A  B    C
0  1  4  7.0
1  2  5  8.0
2  3  6  9.0

print (df.dtypes)
A     object
B      int32
C    float64
dtype: object