代码：使用replace（）方法填充空值

# importing pandas package

import pandas as pd

# making data frame from csv file

data = pd.read_csv("employees.csv")

# Printing the first 10 to 24 rows of

# the data frame for visualization

data[10:25]

输出：

现在我们要用-99值替换数据框中的所有Nan值。

# importing pandas package

import pandas as pd

# making data frame from csv file

data = pd.read_csv("employees.csv")

# will replace Nan value in dataframe with value -99

data.replace(to_replace = np.nan, value = -99)

# importing pandas package

import pandas as pd

# making data frame from csv file

data = pd.read_csv("employees.csv")

# will replace Nan value in dataframe with value -99

data.replace(to_replace = np.nan, value = -99)