Python - 删除 DataFrame 中缺失的 (NaN) 值
要删除缺失值，即NaN值，请使用该dropna()方法。首先，让我们导入所需的库-
import pandas as pd
读取CSV并创建一个DataFrame-
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\CarRecords.csv")使用dropna()删除缺失值。NaN将在dropna()使用后显示缺失值-
dataFrame.dropna()
示例
以下是完整代码
import pandas as pd
#读取csv文件
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\CarRecords.csv")
print("DataFrame with some NaN (missing) values...\n",dataFrame)
#计算DataFrame中的行和列
print("\nNumber of rows and column in our DataFrame = ",dataFrame.shape)
#删除缺失值
print("\nDataFrame after removing NaN values...\n",dataFrame.dropna())输出结果这将产生以下输出-
DataFrame with some NaN (missing) values...
Car Place UnitsSold
0 Audi Bangalore 80.0
1 Porsche Mumbai NaN
2 RollsRoyce Pune 100.0
3 BMW Delhi NaN
4 Mercedes Hyderabad 80.0
5 Lamborghini Chandigarh 80.0
6 Audi Mumbai NaN
7 Mercedes Pune 120.0
8 Lamborghini Delhi 100.0
Number of rows and colums in our DataFrame = (9, 3)
DataFrame after removing NaN values ...
Car Place UnitsSold
0 Audi Bangalore 80.0
2 RollsRoyce Pune 100.0
4 Mercedes Hyderabad 80.0
5 Lamborghini Chandigarh 80.0
7 Mercedes Pune 120.0
8 Lamborghini Delhi 100.0热门推荐
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