10分钟入门Pandas-系列（3）

In []: import pandas as pd
   ...: import numpy as np
   ...:
   ...: df = pd.DataFrame({"id": [, , , , , ],
   ...:                    "raw_grade": ['a', 'b', 'b', 'a', 'a', 'e']})

In []: df["grade"] = df["raw_grade"].astype("category")
   ...: df["grade"]
Out[]:
    a
    b
    b
    a
    a
    e
Name: grade, dtype: category
Categories (, object): [a, b, e]

df["grade"].cat.categories = ["very good", "good", "very bad"]

In []:  df["grade"] = df["grade"].cat.set_categories(["very bad", "bad", "medium",
   ...: "good", "very good"])

In []: df
Out[]:
   id raw_grade      grade
            a  very good
            b       good
            b       good
            a  very good
            a  very good
            e   very bad

In []: df["grade"]
Out[]:
    very good
         good
         good
    very good
    very good
     very bad
Name: grade, dtype: category
Categories (, object): [very bad, bad, medium, good, very good]

In []: df.sort_values(by="grade")
Out[]:
   id raw_grade      grade
            e   very bad
            b       good
            b       good
            a  very good
            a  very good
            a  very good

In []: df.groupby("grade").size()
Out[]:
grade
very bad     
bad          
medium       
good         
very good    
dtype: int64

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

plt.close('all')

ts = pd.Series(np.random.randn(),
               index=pd.date_range('1/1/2000', periods=))

ts = ts.cumsum()

ts.plot()

df = pd.DataFrame(np.random.randn(, ), index=ts.index,
                  columns=['A', 'B', 'C', 'D'])

df = df.cumsum()

plt.figure(); df.plot(); plt.legend(loc='best')

df.to_csv('foo.csv')

 pd.read_csv('foo.csv')

df.to_hdf('foo.h5', 'df')

pd.read_hdf('foo.h5', 'df')

df.head().to_excel('foo.xlsx', sheet_name='Sheet1')

pd.read_excel('foo.xlsx', 'Sheet1', index_col=None, na_values=['NA'])

if pd.Series([False, True, False]):
    print("I was true")

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-16-5c782b38cd2f> in <module>
----> 1 if pd.Series([False, True, False]):
           print("I was true")


D:\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
                "The truth value of a {0} is ambiguous. "
                "Use a.empty, a.bool(), a.item(), a.any() or a.all().".format(
->                  self.__class__.__name__
                )
            )


ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().