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Pandas学习笔记01

30 Dec 2017 |

Pandas学习笔记01

——— Pandas即panel data的缩写

pandas三种数据结构

  • Series
  • DataFrame
  • Panel
数据结构 维度 描述
Series 1 一维标记大小不可变的同质数组
DataFrame 2 通常是二维标记的，大小可变，与潜在的异质列类型的表格结构
Panel 3 通常是三维标记的，大小可变的异质数组

Series

1. 创建一个空Series

# import the pandas library and aliasing as pd
import pandas as pd
s = pd.Series()
print s

Series([], dtype: float64)

2. 从ndarray创建一个Series

# import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array(['a','b','c','d'])
s = pd.Series(data)
print s

0    a
1    b
2    c
3    d
dtype: object

# another example
# import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array(['a','b','c','d'])
s = pd.Series(data,index=[100,101,102,103])
print s

100    a
101    b
102    c
103    d
dtype: object

3. 从字典创建一个Series

# import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = {'a':0.,'b':1.,'c':2.}
s = pd.Series(data)
print s

a    0.0
b    1.0
c    2.0
dtype: float64

# another example
# import ...
import pandas as pd
import numpy as np
data = {'a':0.,'b':1.,'c':2.}
s = pd.Series(data,index=['b','c','d','a'])
print s

b    1.0
c    2.0
d    NaN
a    0.0
dtype: float64

4. 从标量创建一个Series

# import the pandas library and aliasing as pd
import pandas as pd
import numpy as np
s = pd.Series(5,index=[0,1,2,3])
print s

0    5
1    5
2    5
3    5
dtype: int64

5. 按位从Series访问数据

# retrieve the first element
import pandas as pd
s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])
print s[0]

1

# another example
import pandas as pd
s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])

# retrieve the first three element
print s[:3],'\n'

# retrieve the last three element
print s[-3:]

a    1
b    2
c    3
dtype: int64

c    3
d    4
e    5
dtype: int64

6. 使用标签检索数据（索引）

一个Series就像一个固定大小的字典，你可以通过索引获取或者设置元素值

# retrieve a single element
import pandas as pd
s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])
print s['a']

1

# another example
# retrieve multiple elements using a list of index label values
import pandas as pd
s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])
print s[['a','c','d']]

a    1
c    3
d    4
dtype: int64

# if a label is not contained, an exception is raised
import pandas as pd
s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])
print s['f']

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

KeyError                                  Traceback (most recent call last)

<ipython-input-4-bacb63c57eea> in <module>()
      2 import pandas as pd
      3 s = pd.Series([1,2,3,4,5],index=['a','b','c','d','e'])
----> 4 print s['f']


C:\Users\wanghao03\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\core\series.pyc in __getitem__(self, key)
    558     def __getitem__(self, key):
    559         try:
--> 560             result = self.index.get_value(self, key)
    561
    562             if not lib.isscalar(result):


C:\Users\wanghao03\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\indexes\base.pyc in get_value(self, series, key)
   1923                     raise InvalidIndexError(key)
   1924                 else:
-> 1925                     raise e1
   1926             except Exception:  # pragma: no cover
   1927                 raise e1


KeyError: 'f'

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