将 Pandas Dataframe 日期索引和列转换为 Numpy 数组

Question

How can I convert 1 column and the index of a Pandas dataframe with several columns to a Numpy array with the dates lining up with the correct column value from the dataframe?

There are a few issues here with data type and its driving my nuts trying to get both the index and the column out and into the one array!!

Help would be much appreciated!

Answer 1

如果A是数据框和col列：

import pandas as pd output = pd.np.column_stack((A.index.values, A.col.values))

Answer 2

IIUC you need values :

start = pd.to_datetime('2015-02-24')
rng = pd.date_range(start, periods=5)

df = pd.DataFrame({'a': range(5), 'b':list('ABCDE')}, index=rng)  
print (df)
            a  b
2015-02-24  0  A
2015-02-25  1  B
2015-02-26  2  C
2015-02-27  3  D
2015-02-28  4  E

print (df.values)
[[0 'A']
 [1 'B']
 [2 'C']
 [3 'D']
 [4 'E']]

if need index values also first convert datetime to string values in index and then use reset_index for converting index to column:

df.index = df.index.astype(str)
print (df.reset_index().values)
[['2015-02-24' 0 'A']
 ['2015-02-25' 1 'B']
 ['2015-02-26' 2 'C']
 ['2015-02-27' 3 'D']
 ['2015-02-28' 4 'E']]