Question

我有一个要在Python 3.7中的熊猫中转换的csv文件。然后，我想检查某些单元格是否具有NaN（即我的情况下为空），仅在这种情况下，我要用另一个值替换单元格的内容。

我正在选择具有同一行中其他列（列family_name和first_name）中其他单元格内的值的单元格。这是MWE：

import csv
import pandas as pd
import numpy as np
df = pd.DataFrame({"family_name":["smith", "duboule", "dupont"], "first_name":["john","jean-paul", "luc"], "weight":[70, 85, pd.np.nan]})
value_to_replace = 90
if df["weight"][(df["family_name"] == "dupont") & (df["first_name"] == "luc")] == pd.np.nan:
    df["weight"][(df["family_name"] == "dupont") & (df["first_name"] == "luc")] = value_to_replace

我收到以下错误：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/mymac/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py", line 1576, in __nonzero__
    .format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我还尝试了以以下形式添加.bool() == True，但收到了相同的错误消息：

if pd.isna(df["weight"][(df["family_name"] == family_name) & (df["first_name"] == first_name)]).bool() == True:
    df["weight"][(df["family_name"] == "dupont") & (df["first_name"] == "luc")] = value_to_replace

Answer 1

使用np.where

工作方式如下：np.where(condition, true value, false value)

df['weight'] = np.where((df.family_name == 'dupont') & (df.first_name == 'luc'), value_to_replace, df.weight)

print(df)
  family_name first_name  weight
0       smith       john    70.0
1     duboule  jean-paul    85.0
2      dupont        luc    90.0

在OP评论后进行编辑
仅当权重为NaN时，您才能使用.isnull：

df['weight'] = np.where((df.family_name == 'dupont') & (df.first_name == 'luc') & (df.weight.isnull()), value_to_replace, df.weight)

Answer 2

删除所有if语句，并使用它

df.loc[ (df["family_name"] == "dupont") & 
        (df["first_name"] == "luc") & 
        (df["weight"].isnull()), 'weight'] = value_to_replace

我建议您阅读pandas API，以了解loc如何选择/编辑数据

如果对熊猫的一个单元格的陈述给出“系列的真值是模棱两可的”

2 个答案: