【Pandas】检查是否有空值、处理空值

1.创建有空值的DataFrame

import numpy as np
import pandas as pd

dates = pd.date_range("20200307", periods=4)
df1 = pd.DataFrame(np.arange(12).reshape(4, 3), index=dates, columns=["A", "B", "C"])
df2 = pd.DataFrame(df1, index=dates, columns=["A", "B", "C", "D"])  # 新增D列，却不赋值，NaN表示空值
print(df2)
# 打印输出：
#             A   B   C   D
# 2020-03-07  0   1   2 NaN
# 2020-03-08  3   4   5 NaN
# 2020-03-09  6   7   8 NaN
# 2020-03-10  9  10  11 NaN

2.检查是否有空值

print(df2.isnull())  # 是空值返回True，否则返回False
print(np.any(df2.isnull()))  # 只要有一个空值便会返回True，否则返回False
print(np.all(df2.isnull()))  # 全部值都是空值便会返回True，否则返回False
# 输出结果：
#                 A      B      C     D
# 2020-03-07  False  False  False  True
# 2020-03-08  False  False  False  True
# 2020-03-09  False  False  False  True
# 2020-03-10  False  False  False  True
# True
# False

3.给NaN赋值

df2.iloc[0, 3] = 10  # 直接给某个位置赋值
print(df2)
# 打印输出：
#            A   B   C     D
# 2020-03-07  0   1   2  10.0
# 2020-03-08  3   4   5   NaN
# 2020-03-09  6   7   8   NaN
# 2020-03-10  9  10  11   NaN

series = pd.Series([11, 12, 13], index=dates[1:4])
df2["D"] = series  # 同时给D列赋多个值
print(df2)
# 打印输出：
#             A   B   C     D
# 2020-03-07  0   1   2   NaN
# 2020-03-08  3   4   5  11.0
# 2020-03-09  6   7   8  12.0
# 2020-03-10  9  10  11  13.0

4.去除有空值的行或列

df2.loc["2020-03-10", ["A", "B", "C"]] = [11, 12, 15]
df2.fillna("null")  # 把空值填充成null

# dropna(axis,how,subset)方法会删除有空值的行或列，
# axis为0是行，axis为1是列,
# how为any时该行或列只要有一个空值就会删除，all是全都是空值才删除
# subset是一个列表，指定某些列
df2.dropna(axis=0, how="any", subset=["A", "D"])