dataframe插入数据报错SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a
dataframe插入数据报错SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a
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发布于 2019-01-25 14:32:24
发布于 2019-01-25 14:32:24
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。
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原始发表：2018年03月28日，如有侵权请联系 cloudcommunity@tencent.com 删除
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