[英]How to create a dataframe from numpy arrays?
I am trying to create a matrix / DataFrame with the numbers stored in 2 variables 我正在尝试创建一个矩阵/ DataFrame,其中数字存储在2个变量中
x = np.linspace(0,50)
y = np.exp(x)
and I would like them to look like this: 我希望他们看起来像这样:
x | y
___________________
0 | 1.0...
1 | 2.77...
2 | 7.6...
... | ...
50 | 5.18e+21...
I would like it to be in a DataFrame
so I can work with it with the pandas
library. 我希望它在一个DataFrame
所以我可以使用pandas
库。
Thanks in advance 提前致谢
import pandas as pd
df = pd.DataFrame({'x':x, 'y':y})
Change the key in the dictionary to your desired column name. 将字典中的键更改为所需的列名称。
You can do the following. 您可以执行以下操作。
import pandas as pd
import numpy as np
df = pd.DataFrame()
df['x'] = np.linspace(0,50)
df['y'] = np.exp(df['x'])
With pandas
: 有了pandas
:
You can issue 你可以发行
>>> xs = np.arange(51)
>>> ys = np.exp(xs)
to get the x and y values and then build your dataframe with 获取x和y值,然后使用。来构建数据框
>>> df = pd.DataFrame({'x': xs, 'y': ys})
>>> df
x y
0 0 1.000000e+00
1 1 2.718282e+00
2 2 7.389056e+00
3 3 2.008554e+01
...
In this case, you can also use the x-values as the index of a series without losing any information. 在这种情况下,您还可以使用x值作为系列的索引而不会丢失任何信息。
>>> index = pd.RangeIndex(0, 51, name='x')
>>> exps = pd.Series(data=np.exp(index), index=index, name='y')
>>> exps
x
0 1.000000e+00
1 2.718282e+00
2 7.389056e+00
3 2.008554e+01
...
Name: y, dtype: float64
Without pandas
: 没有pandas
:
Consider if you truly need a dataframe or series. 考虑一下您是否真的需要数据帧或系列。 You could just leave it at 你可以把它留在
>>> xs = np.arange(51)
>>> ys = np.exp(xs)
and then index into ys
with the integers 0
, 1
, 2
, ... to get the values of exp(0)
, exp(1)
, exp(2)
, ... 然后索引ys
与整数0
, 1
, 2
,...得到的值exp(0)
exp(1)
exp(2)
,...
Simply: 只是:
Code: 码:
import pandas as pd
import numpy as np
x = np.linspace(0,50)
y = np.exp(x)
df = pd.DataFrame({'x': x, 'y': y})
Just make a list of tuples and pass it to the DataFrame
constructor: 只需创建一个元组列表并将其传递给DataFrame
构造函数:
df = pd.DataFrame([(i, np.exp(i)) for i in np.linspace(0,50)], columns=['x', 'y'])
Output 产量
x y
0 1.000000e+00
1 2.718282e+00
2 7.389056e+00
...
What you are looking for is [np.concatenate][1]
. 你要找的是[np.concatenate][1]
。
So for your example, the code would be 因此,对于您的示例,代码将是
import numpy as np
x = np.linspace(0,50)
y = np.exp(x)
z = np.concatenate((x.reshape(1,-1),y.reshape(1,-1))).T
print(z.shape)
# (2,50)
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