(84)--制作数据面板

# 制作数据面板

df1 = pd.read_csv(r'Desktop\1.csv')

df1
Out[90]: 
     a   b   c   d
0    3   5   8   4
1    4   6   9   5
2    5   7  10   6
3    6   8  11   7
4    7   9  12   8
5    8  10  13   9
6    9  11  14  10
7   10  12  15  11
8   11  13  16  12
9   12  14  17  13
10  13  15  18  14
11  14  16  19  15
12  15  17  20  16

df2 = pd.read_csv(r'Desktop\2.csv')

df2
Out[92]: 
     a   b   c   d
0    8   4   7   2
1    9   5   8   3
2   10   6   9   4
3   11   7  10   5
4   12   8  11   6
5   13   9  12   7
6   14  10  13   8
7   15  11  14   9
8   16  12  15  10
9   17  13  16  11
10  18  14  17  12
11  19  15  18  13
12  20  16  19  14

dff = {'item1':df1,'item2':df2}

dff
Out[94]: 
{'item1':      a   b   c   d
 0    3   5   8   4
 1    4   6   9   5
 2    5   7  10   6
 3    6   8  11   7
 4    7   9  12   8
 5    8  10  13   9
 6    9  11  14  10
 7   10  12  15  11
 8   11  13  16  12
 9   12  14  17  13
 10  13  15  18  14
 11  14  16  19  15
 12  15  17  20  16, 'item2':      a   b   c   d
 0    8   4   7   2
 1    9   5   8   3
 2   10   6   9   4
 3   11   7  10   5
 4   12   8  11   6
 5   13   9  12   7
 6   14  10  13   8
 7   15  11  14   9
 8   16  12  15  10
 9   17  13  16  11
 10  18  14  17  12
 11  19  15  18  13
 12  20  16  19  14}

pd.Panel(dff)
Out[95]: 
<class 'pandas.core.panel.Panel'>
Dimensions: 2 (items) x 13 (major_axis) x 4 (minor_axis)
Items axis: item1 to item2
Major_axis axis: 0 to 12
Minor_axis axis: a to d

# 第二种表示方法

 df1 = pd.read_csv(r'Desktop\1.csv')

df1
Out[97]: 
     a   b   c   d
0    3   5   8   4
1    4   6   9   5
2    5   7  10   6
3    6   8  11   7
4    7   9  12   8
5    8  10  13   9
6    9  11  14  10
7   10  12  15  11
8   11  13  16  12
9   12  14  17  13
10  13  15  18  14
11  14  16  19  15
12  15  17  20  16

df2 = pd.read_csv(r'Desktop\2.csv')

df2
Out[99]: 
     a   b   c   d
0    8   4   7   2
1    9   5   8   3
2   10   6   9   4
3   11   7  10   5
4   12   8  11   6
5   13   9  12   7
6   14  10  13   8
7   15  11  14   9
8   16  12  15  10
9   17  13  16  11
10  18  14  17  12
11  19  15  18  13
12  20  16  19  14

dff = np.array([np.array(df1),np.array(df2)])

dff
Out[101]: 
array([[[ 3,  5,  8,  4],
        [ 4,  6,  9,  5],
        [ 5,  7, 10,  6],
        [ 6,  8, 11,  7],
        [ 7,  9, 12,  8],
        [ 8, 10, 13,  9],
        [ 9, 11, 14, 10],
        [10, 12, 15, 11],
        [11, 13, 16, 12],
        [12, 14, 17, 13],
        [13, 15, 18, 14],
        [14, 16, 19, 15],
        [15, 17, 20, 16]],

       [[ 8,  4,  7,  2],
        [ 9,  5,  8,  3],
        [10,  6,  9,  4],
        [11,  7, 10,  5],
        [12,  8, 11,  6],
        [13,  9, 12,  7],
        [14, 10, 13,  8],
        [15, 11, 14,  9],
        [16, 12, 15, 10],
        [17, 13, 16, 11],
        [18, 14, 17, 12],
        [19, 15, 18, 13],
        [20, 16, 19, 14]]], dtype=int64)

pd.Panel(dff,items=['item1','item2'],major_axis=[np.arange(13)],minor_axis=['a','b','c','d'])
Out[102]: 
<class 'pandas.core.panel.Panel'>
Dimensions: 2 (items) x 13 (major_axis) x 4 (minor_axis)
Items axis: item1 to item2
Major_axis axis: 0 to 12
Minor_axis axis: a to d

兄弟连学python


Python学习交流、资源共享群:563626388 QQ


猜你喜欢

转载自blog.csdn.net/fredreck1919/article/details/80230821