Pandas使用NumPy NaN（np.nan）对象表示缺失值。这是一个不等于自身的特殊对象
np.nan == np.nan
#False
Python的None对象是等于自身的
None == None
#True
所有和np.nan的比较都返回False，除了不等于：
9 > np.nan
#False
5 != np.nan
#True
college_ugds_所有值和.0019比较，返回布尔值DataFrame
college = pd.read_csv('data/college.csv', index_col='INSTNM')
college_ugds_ = college.filter(like='UGDS_')
college_ugds_.head() == .0019
UGDS_WHITEUGDS_BLACKUGDS_HISPUGDS_ASIANUGDS_AIANUGDS_NHPIUGDS_2MORUGDS_NRAUGDS_UNKNINSTNM Alabama A & M UniversityFalseFalseFalseTrueFalseTrueFalseFalseFalseUniversity of Alabama at BirminghamFalseFalseFalseFalseFalseFalseFalseFalseFalseAmridge UniversityFalseFalseFalseFalseFalseFalseFalseFalseFalseUniversity of Alabama in HuntsvilleFalseFalseFalseFalseFalseFalseFalseFalseFalseAlabama State UniversityFalseFalseFalseTrueFalseFalseFalseFalseFalse
用DataFrame和DataFrame进行比较
用DataFrame和DataFrame进行比较
college_self_compare = college_ugds_ == college_ugds_
college_self_compare.head()
UGDS_WHITEUGDS_BLACKUGDS_HISPUGDS_ASIANUGDS_AIANUGDS_NHPIUGDS_2MORUGDS_NRAUGDS_UNKNINSTNM Alabama A & M UniversityTrueTrueTrueTrueTrueTrueTrueTrueTrueUniversity of Alabama at BirminghamTrueTrueTrueTrueTrueTrueTrueTrueTrueAmridge UniversityTrueTrueTrueTrueTrueTrueTrueTrueTrueUniversity of Alabama in HuntsvilleTrueTrueTrueTrueTrueTrueTrueTrueTrueAlabama State UniversityTrueTrueTrueTrueTrueTrueTrueTrueTrue
用all()检查是否所有的值都是True；这是因为缺失值不互相等于
用all()检查是否所有的值都是True；这是因为缺失值不互相等于。
college_self_compare.all()
UGDS_WHITE False
UGDS_BLACK False
UGDS_HISP False
UGDS_ASIAN False
UGDS_AIAN False
UGDS_NHPI False
UGDS_2MOR False
UGDS_NRA False
UGDS_UNKN False
dtype: bool
可以用==号判断，然后求和
可以用==号判断，然后求和
(college_ugds_ == np.nan).sum()
UGDS_WHITE 0
UGDS_BLACK 0
UGDS_HISP 0
UGDS_ASIAN 0
UGDS_AIAN 0
UGDS_NHPI 0
UGDS_2MOR 0
UGDS_NRA 0
UGDS_UNKN 0
dtype: int64
统计缺失值最主要方法是使用isnull方法：
统计缺失值最主要方法是使用isnull方法：
college_ugds_.isnull().sum()
UGDS_WHITE 661
UGDS_BLACK 661
UGDS_HISP 661
UGDS_ASIAN 661
UGDS_AIAN 661
UGDS_NHPI 661
UGDS_2MOR 661
UGDS_NRA 661
UGDS_UNKN 661
dtype: int64
比较两个DataFrame最直接的方法是使用equals()方法
比较两个DataFrame最直接的方法是使用equals()方法
from pandas.testing import assert_frame_equal
assert_frame_equal(college_ugds_, college_ugds_)
eq()方法类似于==，和前面的equals有所不同
college_ugds_.eq(.0019).head()
UGDS_WHITEUGDS_BLACKUGDS_HISPUGDS_ASIANUGDS_AIANUGDS_NHPIUGDS_2MORUGDS_NRAUGDS_UNKNINSTNM Alabama A & M UniversityFalseFalseFalseTrueFalseTrueFalseFalseFalseUniversity of Alabama at BirminghamFalseFalseFalseFalseFalseFalseFalseFalseFalseAmridge UniversityFalseFalseFalseFalseFalseFalseFalseFalseFalseUniversity of Alabama in HuntsvilleFalseFalseFalseFalseFalseFalseFalseFalseFalseAlabama State UniversityFalseFalseFalseTrueFalseFalseFalseFalseFalse
Original: https://blog.csdn.net/weixin_48135624/article/details/113828860
Author: 缘 源 园
Title: DataFrame的比较和缺失值比较
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