将函数应用于 Pandas Python 中的每一行时发生数据转换错误 [英] Data Conversion Error while applying a function to each row in pandas Python

问题描述

我在 python 中的 Pandas 中有一个数据框，它类似于这样的东西 -

I have a data frame in pandas in python which resembles something like this -

    contest_login_count  contest_participation_count  ipn_ratio
0                    1                            1   0.000000
1                    3                            3   0.083333
2                    3                            3   0.000000
3                    3                            3   0.066667
4                    5                           13   0.102804
5                    2                            3   0.407407
6                    1                            3   0.000000
7                    1                            2   0.000000
8                   53                           91   0.264151
9                    1                            2   0.000000

现在我想对这个数据框的每一行应用一个函数函数是这样写的 -

Now I want to apply a function to each row of this dataframe The function is written as this -

def findCluster(clusterModel,data):
    return clusterModel.predict(data)

我以这种方式将此函数应用于每一行 -

I apply this function to each row in this manner -

df_fil.apply(lambda x : findCluster(cluster_all,x.reshape(1,-1)),axis=1)

当我运行此代码时，我收到一条警告说 -

When I run this code, I get a warning saying -

DataConversionWarning:具有输入 dtype 对象的数据已转换为 float64.

DataConversionWarning: Data with input dtype object was converted to float64.

warnings.warn(msg, DataConversionWarning)

warnings.warn(msg, DataConversionWarning)

此警告每行打印一次.因为，我的数据框中有大约 450K 行，所以我的计算机在 ipython 笔记本上打印所有这些警告消息时挂起.

This warning is printed once for each row. Since, I have around 450K rows in my data frame, my computer hangs while printing all these warning messages that too on ipython notebook.

但是为了测试我的功能，我创建了一个虚拟数据框并尝试对其应用相同的功能，并且效果很好.这是代码 -

But to test my function I created a dummy dataframe and tried applying the same function on that and it works well. Here is the code for that -

t = pd.DataFrame([[10.35,100.93,0.15],[10.35,100.93,0.15]])
t.apply(lambda x:findCluster(cluster_all,x.reshape(1,-1)),axis=1)

输出结果是 -

   0  1  2
0  4  4  4
1  4  4  4

任何人都可以建议我做错了什么，或者我可以改变什么来消除这个错误?

Can anyone suggest what am I doing wrong or what can I change to make this error go away?

推荐答案

我觉得有些列的dtype不是float有问题.

I think there is problem dtype of some column is not float.

你需要通过 astype:

You need cast it by astype:

df['colname'] = df['colname'].astype(float)

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