pandas 数据框到numpy数组 [英] Pandas dataframe to numpy array
问题描述
我是Python的新手,经验不足.我已经设法通过复制,粘贴和替换已有的数据来使一些代码正常工作,但是我一直在寻找如何从数据框中选择数据的方法,但无法理解示例并替换我自己的数据.
I am very new to Python and have very little experience. I've managed to get some code working by copying and pasting and substituting the data I have, but I've been looking up how to select data from a dataframe but can't make sense of the examples and substitute my own data in.
总体目标 :(如果有人真的可以帮我写整件事,那会很有帮助,但可能性很小,而且很可能不允许)
The overarching goal: (if anyone could actually help me write the entire thing, that would be helpful, but highly unlikely and probably not allowed)
当两种化学物质发生反应时,我试图使用scipy
拟合温度变化曲线.有40个试验.我希望使用的模型是具有六个参数的广义逻辑函数.我需要的只是40个功能,仅此而已.我不知道如何实现这一目标,但是当我到达那里时,我会问另一个问题.
I am trying to use scipy
to fit the curve of a temperature change when two chemicals react. There are 40 trials. The model I am hoping to use is a generalized logistic function with six parameters. All I need are the 40 functions, and nothing else. I have no idea how to achieve this, but I will ask another question when I get there.
当前问题:
我导入了40个.csv
文件,将数据编译/缩短为2个部分,因此1个文件中有20个试验.现在数据有21列和63行.每列的第一行中都有一个标题,并且第一列是一致的时间间隔.
I had imported 40 .csv
files, compiled/shortened the data into 2 sections so that there are 20 trials in 1 file. Now the data has 21 columns and 63 rows. There is a title in the first row for each column, and the first column is a consistent time interval.
但是,每次审判不一定要那么长.不过其中之一确实如此.因此,我设法为数据框编写以下代码:
However, each trial is not necessarily that long. One of them does, though. So I've managed to write the following code for a dataframe:
import pandas as pd
df = pd.read_csv("~/Truncated raw data hcl.csv")
print(df)
它会打印出表格,但是正如预期的那样,存在没有数据的NaN.
It prints the table out, but as expected, there are NaNs where there exists no data.
所以我想知道如何将其排列成具有2列,时间和(x,y)的图的试验数组,以便将来使用numpy
或scipy
进行工作,从而使行没有任何数据将不包括在内.
So I would like to know how to arrange it into workable array with 2 columns , time and a trial like an (x,y) for a graph for future workings with numpy
or scipy
such that the rows that there is no data would not be included.
.csv
文件的一部分在水平线之后开始.我太懒了,无法将其放在代码块中,对不起.谢谢.
Part of the .csv
file begins after the horizontal line. I'm too lazy to put it in a code block, sorry. Thank you.
time,1mnaoh trial 1,1mnaoh trial 2,1mnaoh trial 3,1mnaoh trial 4,2mnaoh trial 1,2mnaoh trial 2,2mnaoh trial 3,2mnaoh trial 4,3mnaoh trial 1,3mnaoh trial 2,3mnaoh trial 3,3mnaoh trial 4,4mnaoh trial 1,4mnaoh trial 2,4mnaoh trial 3,4mnaoh trial 4,5mnaoh trial 1,5mnaoh trial 2,5mnaoh trial 3,5mnaoh trial 4
0.0,23.2,23.1,23.1,23.8,23.1,23.1,23.3,22.0,22.8,23.4,23.3,24.0,23.0,23.8,23.8,24.0,23.3,24.3,24.1,24.1
0.5,23.2,23.1,23.1,23.8,23.1,23.1,23.3,22.1,22.8,23.4,23.3,24.0,23.0,23.8,23.8,24.0,23.4,24.3,24.1,24.1
1.0,23.2,23.1,23.1,23.7,23.1,23.1,23.3,22.3,22.8,23.4,23.3,24.0,23.0,23.8,23.8,24.0,23.5,24.3,24.1,24.1
1.5,23.2,23.1,23.1,23.7,23.1,23.1,23.3,22.4,22.8,23.4,23.3,24.0,23.0,23.8,23.8,23.9,23.6,24.3,24.1,24.1
2.0,23.3,23.2,23.2,24.2,23.6,23.2,24.3,22.5,23.0,23.7,24.4,24.1,23.1,23.9,24.4,24.2,23.7,24.5,24.7,25.1
2.5,24.0,23.5,23.5,25.4,25.3,23.3,26.4,22.7,23.5,25.8,27.9,25.1,23.1,23.9,27.4,26.8,23.8,27.2,26.7,28.1
3.0,25.4,24.4,24.1,26.5,27.8,23.3,28.5,22.8,24.6,28.6,31.2,27.2,23.2,23.9,30.9,30.5,23.9,31.4,29.8,31.3
3.5,26.9,25.5,25.1,27.4,29.9,23.4,30.1,22.9,26.4,31.4,34.0,30.0,23.3,24.2,33.8,34.0,23.9,35.1,33.2,34.4
4.0,27.8,26.5,26.2,27.9,31.4,23.4,31.3,23.1,28.8,34.0,36.1,32.6,23.3,26.6,36.0,36.7,24.0,37.7,35.9,36.8
4.5,28.5,27.3,27.0,28.2,32.6,23.5,32.3,23.1,31.2,36.0,37.5,34.8,23.4,30.0,37.7,38.7,24.0,39.7,38.0,38.7
5.0,28.9,27.9,27.7,28.5,33.4,23.5,33.1,23.2,33.2,37.6,38.6,36.5,23.4,33.2,39.0,40.2,24.0,40.9,39.6,40.2
5.5,29.2,28.2,28.3,28.9,34.0,23.5,33.7,23.3,35.0,38.7,39.4,37.9,23.5,35.6,39.9,41.2,24.0,41.9,40.7,41.0
6.0,29.4,28.5,28.6,29.1,34.4,24.9,34.2,23.3,36.4,39.6,40.0,38.9,23.5,37.3,40.6,42.0,24.1,42.5,41.6,41.2
6.5,29.5,28.8,28.9,29.3,34.7,27.0,34.6,23.3,37.6,40.4,40.4,39.7,23.5,38.7,41.1,42.5,24.1,43.1,42.3,41.7
7.0,29.6,29.0,29.1,29.5,34.9,28.8,34.8,23.5,38.6,40.9,40.8,40.2,23.5,39.7,41.4,42.9,24.1,43.4,42.8,42.3
7.5,29.7,29.2,29.2,29.6,35.1,30.5,35.0,24.9,39.3,41.4,41.1,40.6,23.6,40.5,41.7,43.2,24.0,43.7,43.1,42.9
8.0,29.8,29.3,29.3,29.7,35.2,31.8,35.2,26.9,40.0,41.6,41.3,40.9,23.6,41.1,42.0,43.4,24.2,43.8,43.3,43.3
8.5,29.8,29.4,29.4,29.8,35.3,32.8,35.4,28.9,40.5,41.8,41.4,41.2,23.6,41.6,42.2,43.5,27.0,43.9,43.5,43.6
9.0,29.9,29.5,29.5,29.9,35.4,33.6,35.5,30.5,40.8,41.8,41.6,41.4,23.6,41.9,42.4,43.7,30.8,44.0,43.6,43.8
9.5,29.9,29.6,29.5,30.0,35.5,34.2,35.6,31.7,41.0,41.8,41.7,41.5,23.6,42.2,42.5,43.7,33.9,44.0,43.7,44.0
10.0,30.0,29.7,29.6,30.0,35.5,34.6,35.7,32.7,41.1,41.9,41.8,41.7,23.6,42.4,42.6,43.8,36.2,44.0,43.7,44.1
10.5,30.0,29.7,29.6,30.1,35.6,35.0,35.7,33.3,41.2,41.9,41.8,41.8,23.6,42.6,42.6,43.8,37.9,44.0,43.8,44.2
11.0,30.0,29.7,29.6,30.1,35.7,35.2,35.8,33.8,41.3,41.9,41.9,41.8,24.0,42.9,42.7,43.8,39.3,,43.8,44.3
11.5,30.0,29.8,29.7,30.1,35.8,35.4,35.8,34.1,41.4,41.9,42.0,41.8,26.6,43.1,42.7,43.9,40.2,,43.8,44.3
12.0,30.0,29.8,29.7,30.1,35.8,35.5,35.9,34.3,41.4,42.0,42.0,41.9,30.3,43.3,42.7,43.9,40.9,,43.9,44.3
12.5,30.1,29.8,29.7,30.2,35.9,35.7,35.9,34.5,41.5,42.0,42.0,,33.4,43.4,42.7,44.0,41.4,,43.9,44.3
13.0,30.1,29.8,29.8,30.2,35.9,35.8,36.0,34.7,41.5,42.0,42.1,,35.8,43.5,42.7,44.0,41.8,,43.9,44.4
13.5,30.1,29.9,29.8,30.2,36.0,36.0,36.0,34.8,41.5,42.0,42.1,,37.7,43.5,42.8,44.1,42.0,,43.9,44.4
14.0,30.1,29.9,29.8,30.2,36.0,36.1,36.0,34.9,41.6,,42.2,,39.0,43.5,42.8,44.1,42.1,,,44.4
14.5,,29.9,29.8,,36.0,36.2,36.0,35.0,41.6,,42.2,,40.0,43.5,42.8,44.1,42.3,,,44.4
15.0,,29.9,,,36.0,36.3,,35.0,41.6,,42.2,,40.7,,42.8,44.1,42.4,,,
15.5,,,,,36.0,36.4,,35.1,41.6,,42.2,,41.3,,,,42.4,,,
推荐答案
要将整个DataFrame
转换为numpy数组,请使用
To convert a whole DataFrame
into a numpy array, use
df = df.values()
如果我正确理解了您的意思,尽管您每次尝试都希望使用单独的数组.可以这样完成:
If i understood you correctly, you want seperate arrays for every trial though. This can be done like this:
data = [df.iloc[:, [0, i]].values() for i in range(1, 20)]
这将创建一个numpy数组的列表,每个数组都包含带有温度的第一列和一个试验列.
which will make a list of numpy arrays, every one containing the first column with temperature and one of the trial columns.
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