如何在Python中处理数据中的NaN值？

Question

我有一个很大的数据集，其中包含多个列中的许多NaN值。

我尝试了以下代码，但它没有从数据集中删除Nan值

df = pd.read_excel('sec3_data.xlsx')
df.dropna(subset=["Deviation from Partisanship"])
df['Deviation from Partisanship'].unique()

输出：

array([nan, 'Vote for opposing party', 'Vote for own party'], dtype=object)

它清楚地表明仍然有一些nan值可用。如何删除它们？

Answer 1

您需要重新分配到新的数据框：

df2 = df.dropna(subset=["Deviation from Partisanship"])

或执行放置inplace：

df.dropna(subset=["Deviation from Partisanship"], inplace=True)

您可以在以下文档中找到更多信息：https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html

Answer 2

您需要将其写为

df = df.dropna(subset=["Deviation from Partisanship"])

或

df.dropna(subset=["Deviation from Partisanship"], inplace=True)

Answer 3

# Method 1
df = pd.read_excel('sec3_data.xlsx')
df.dropna(subset=["Deviation from Partisanship"], inplace=True)
df['Deviation from Partisanship'].unique()

# Method 2
df = pd.read_excel('sec3_data.xlsx')
df2 = df.dropna(subset=["Deviation from Partisanship"])
df2['Deviation from Partisanship'].unique()