pandas 文档自用3

 tsdf.transform(np.abs)    应用函数

 tsdf.A.transform([np.abs, lambda x: x + 1])

tsdf.transform({'A': np.abs, 'B': lambda x: x + 1})

 tsdf.transform({'A': np.abs, 'B': [lambda x: x + 1, 'sqrt']})

df4['one'].map(f)

df4.applymap(f)

map方法还可以做映射

s = pd.Series(['six', 'seven', 'six', 'seven', 'six'],index=['a', 'b', 'c', 'd', 'e'])

t = pd.Series({'six': 6., 'seven': 7.})

s.map(t)  把six和seven映射成6和7

Reindexing and altering labels

s.reindex(['e', 'b', 'f', 'd'])

df.reindex(index=['c', 'f', 'b'], columns=['three', 'two', 'one'])

df.reindex(['c', 'f', 'b'], axis='index')

s.reindex(df.index)
df.reindex_like(df2)
s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
 s1 = s[:4]
 s2 = s[1:]
s1.align(s2)
ts2.reindex(ts.index, method='ffill', limit=1)
ts2.reindex(ts.index, method='ffill', tolerance='1 day')
df.drop(['a', 'd'], axis=0)
df.drop(['one'], axis=1)
 df.reindex(df.index.difference(['a', 'd']))
# 映射标签 对于series
s.rename(str.upper)
 df.rename(columns={'one': 'foo', 'two': 'bar'},index={'a': 'apple', 'b': 'banana', 'd': 'durian'})
# rename使用的时候没有的标签不会报错
index=pd.MultiIndex.from_product([['a', 'b', 'c'], [1, 2]]
df.rename_axis(index={'let': 'abc'})
df.rename_axis(index=str.upper)