dataframe插入数据报错SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a

SettingWithCopyWarning 解决方案

场景

问题场景：我在读取csv文件之后，因为要新增一个特征列并根据已有特征修改新增列的值，结果在修改的时候就碰到了SettingWithCopyWarning这个警告，花了很长时间才解决这个问题。

案例：

import pandas as pd
import numpy as np

aa = np.array([1, 0, 1, 0])
bb = pd.DataFrame(aa.T, columns=['one'])
print(bb)
   one
0    1
1    0
2    1
3    0
bb['two'] = 0
print(bb)
   one  two
0    1    0
1    0    0
2    1    0
3    0    0

按条件修改新列再输出就报错了：

for i in range(bb.shape[0]):
    if bb['one'][i] == 0:
        bb['two'][i] = 1
print(bb)

C:/PycharmProjects/NaiveBayesProduct/pandas/try_index.py:22: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  bb['two'][i] = 1
   one  two
0    1    0
1    0    1
2    1    0
3    0    1

解决方案

正确方案应该是生成好正确的数组再插入dataframe中。下面我把上面的例子用正确地方法再重新生成一遍。

import pandas as pd
import numpy as np

aa = np.array([1, 0, 1, 0])
bb = pd.DataFrame(aa.T, columns=['one'])
# 生成一个ndarray，装要插入的值
two = np.zeros(bb.shape[0])
# 按条件修改two
for i in range(bb.shape[0]):
    if bb['one'][i] == 0:
        two[i] = 1
# 完成后将two插入dataframe中
bb.insert(1,'two', two)  
 #insert 三个参数，插到第几列，该列列名，如果是bb.insert(0,'two', two)，插入到第一列，
print(bb)

   one  two
0    1  0.0
1    0  1.0
2    1  0.0
3    0  1.0

个人代码

个人案例代码：在进行利用朴素贝叶斯网络进行对评论进行分类的过程中，正向定义为1，负向定义为0.插入评论分析结果时报错

comm_data=pd.read_csv("C:\\Users\\lenovo\\Desktop\\comm\\new_data.csv",encoding="utf-8")
        # comm_data=new_data
        print(comm_data.head(5))
        comm_data["classify"]="#"
        for c in range(len(comm_data)):
            classify=testingNB(comm_data["content"][c])
            # print(classify)
            comm_data["classify"][c]=classify
        comm_data.to_csv("C:\\Users\\lenovo\\Desktop\\comm\\comm_data.csv")

出现报错：

D:/office3/python/python_py/compare/score_variance/get_data/web5_data_mg.py:161: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  comm_data["classify"][c]=classify

解决方案;

    comm_data=pd.read_csv("C:\\Users\\lenovo\\Desktop\\comm\\new_data.csv",encoding="utf-8")
        # comm_data=new_data
        print(comm_data.head(5))
        # comm_data["classify"]="#"
        classify= np.zeros(comm_data.shape[0])
        for c in range(len(comm_data)):
            classifynb=testingNB(comm_data["content"][c])
            # print(classify)
            # comm_data["classify"][c]=classify
            classify[c]=classifynb
        comm_data(0,'classify', classify)
        comm_data.to_csv("C:\\Users\\lenovo\\Desktop\\comm\\comm_data.csv")

这样问题就解决了。