2020-10-19 21:08:55

docs/da/152.md

@@ -2,7 +2,7 @@
 
 In [1]:
 
-```
+```py
 import numpy as np
 import pandas as pd
 
@@ -12,7 +12,7 @@ import pandas as pd
 
 作为一维结构，它的索引叫做 `index`，基本调用方法为
 
-```
+```py
 s = pd.Series(data, index=index) 
 ```
 
@@ -30,7 +30,7 @@ s = pd.Series(data, index=index)
 
 In [2]:
 
-```
+```py
 s = pd.Series(np.random.randn(5), index=["a", "b", "c", "d", "e"])
 
 s
@@ -39,7 +39,7 @@ s
 
 Out[2]:
 
-```
+```py
 a   -0.032806
 b    0.050207
 c   -1.909697
@@ -52,14 +52,14 @@ dtype: float64
 
 In [3]:
 
-```
+```py
 s.index
 
 ```
 
 Out[3]:
 
-```
+```py
 Index([u'a', u'b', u'c', u'd', u'e'], dtype='object')
 ```
 
@@ -67,14 +67,14 @@ Index([u'a', u'b', u'c', u'd', u'e'], dtype='object')
 
 In [4]:
 
-```
+```py
 pd.Series(np.random.randn(5))
 
 ```
 
 Out[4]:
 
-```
+```py
 0   -0.376233
 1   -0.474349
 2    1.660590
@@ -89,7 +89,7 @@ dtype: float64
 
 In [5]:
 
-```
+```py
 d = {'a' : 0., 'b' : 1., 'c' : 2.}
 
 pd.Series(d)
@@ -98,7 +98,7 @@ pd.Series(d)
 
 Out[5]:
 
-```
+```py
 a    0
 b    1
 c    2
@@ -109,14 +109,14 @@ dtype: float64
 
 In [6]:
 
-```
+```py
 pd.Series(d, index=['b', 'd', 'a'])
 
 ```
 
 Out[6]:
 
-```
+```py
 b     1
 d   NaN
 a     0
@@ -129,14 +129,14 @@ dtype: float64
 
 In [7]:
 
-```
+```py
 pd.Series(5., index=['a', 'b', 'c', 'd', 'e'])
 
 ```
 
 Out[7]:
 
-```
+```py
 a    5
 b    5
 c    5
@@ -149,14 +149,14 @@ dtype: float64
 
 In [8]:
 
-```
+```py
 s
 
 ```
 
 Out[8]:
 
-```
+```py
 a   -0.032806
 b    0.050207
 c   -1.909697
@@ -169,14 +169,14 @@ dtype: float64
 
 In [9]:
 
-```
+```py
 s[0]
 
 ```
 
 Out[9]:
 
-```
+```py
 -0.032806330572971713
 ```
 
@@ -184,14 +184,14 @@ Out[9]:
 
 In [10]:
 
-```
+```py
 s[:3]
 
 ```
 
 Out[10]:
 
-```
+```py
 a   -0.032806
 b    0.050207
 c   -1.909697
@@ -202,14 +202,14 @@ dtype: float64
 
 In [11]:
 
-```
+```py
 s[s > s.median()]
 
 ```
 
 Out[11]:
 
-```
+```py
 a   -0.032806
 b    0.050207
 dtype: float64
@@ -219,14 +219,14 @@ dtype: float64
 
 In [12]:
 
-```
+```py
 s[[4, 3, 1]]
 
 ```
 
 Out[12]:
 
-```
+```py
 e   -0.073793
 d   -1.127865
 b    0.050207
@@ -237,14 +237,14 @@ dtype: float64
 
 In [13]:
 
-```
+```py
 np.exp(s)
 
 ```
 
 Out[13]:
 
-```
+```py
 a    0.967726
 b    1.051488
 c    0.148125
@@ -259,14 +259,14 @@ dtype: float64
 
 In [14]:
 
-```
+```py
 s["a"]
 
 ```
 
 Out[14]:
 
-```
+```py
 -0.032806330572971713
 ```
 
@@ -274,7 +274,7 @@ Out[14]:
 
 In [15]:
 
-```
+```py
 s["e"] = 12.
 
 s
@@ -283,7 +283,7 @@ s
 
 Out[15]:
 
-```
+```py
 a    -0.032806
 b     0.050207
 c    -1.909697
@@ -296,27 +296,27 @@ dtype: float64
 
 In [16]:
 
-```
+```py
 "e" in s
 
 ```
 
 Out[16]:
 
-```
+```py
 True
 ```
 
 In [17]:
 
-```
+```py
 "f" in s
 
 ```
 
 Out[17]:
 
-```
+```py
 False
 ```
 
@@ -324,14 +324,14 @@ False
 
 In [18]:
 
-```
+```py
 s.get("f", np.nan)
 
 ```
 
 Out[18]:
 
-```
+```py
 nan
 ```
 
@@ -341,14 +341,14 @@ nan
 
 In [19]:
 
-```
+```py
 s + s
 
 ```
 
 Out[19]:
 
-```
+```py
 a    -0.065613
 b     0.100413
 c    -3.819395
@@ -359,14 +359,14 @@ dtype: float64
 
 In [20]:
 
-```
+```py
 s * 2
 
 ```
 
 Out[20]:
 
-```
+```py
 a    -0.065613
 b     0.100413
 c    -3.819395
@@ -379,14 +379,14 @@ dtype: float64
 
 In [21]:
 
-```
+```py
 s[1:] + s[:-1]
 
 ```
 
 Out[21]:
 
-```
+```py
 a         NaN
 b    0.100413
 c   -3.819395
@@ -403,7 +403,7 @@ dtype: float64
 
 In [22]:
 
-```
+```py
 s = pd.Series(np.random.randn(5), name='something')
 s.name
 
@@ -411,6 +411,6 @@ s.name
 
 Out[22]:
 
-```
+```py
 'something'
 ```