Micro Series 8051 C-Compiler V4.10A/DOS (c) Copyright IAR Systems 1991 Usage: icc8051 {} {} Sourcefile: 'C' source file with default extension: .c Environment: QCC8051 Options (specified order is of no importance): -o file Put object on: -Oprefix
B-L475E-IOT01A开发板用户手册,非常详尽，附有10多页的完整原理图，每个模块功能介绍很详细，不错的学习资料UM2153
Contents
7.12.2 Capacitive digital sensor for relative humidity and
temperature(HTS221)
25
7. 12.3 High-performance 3-axis magnetometer(LIS3MDL
25
7. 12. 4 3D accelerometer and 3D gyro
Intel RealSense D400系列摄像头使用文档 /Intel RealSense D400系列摄像头使用文档Descr iption and Features
intel REALSENSE
TECHNOLOGY
Contents
Descr iption and Features
11
Introduction
.12
2.1
Purpose and scope of this document
■■■画画
12
Terminology
12
2.3 Stereo Vision D
如下所示：
import numpy as np
import pandas as pd
from pandas import Series,DataFrame
一、drop方法：产生新对象
1.Series
o = Series([1,3,4,7],index=['d','c','b','a'])
print(o.drop(['d','b']))
c 3
a 7
dtype: int64
2.DataFrame
data = {'水果':['苹果','梨','草莓'],
'
如下所示：
import numpy as np
import pandas as pd
from pandas import Series,DataFrame
一、Series与Series
s1 = Series([1,3,5,7],index=['a','b','c','d'])
s2 = Series([2,4,6,8],index=['a','b','c','e'])
索引对齐项相加，不对齐项的值取NaN
s1+s2
1
a 3.0
b 7.0
c 11.0
d NaN
e
遍历pd.Series的index和value的方法如下，python built-in list的enumerate方法不管用
for i, v in s.items():
print('index: ', i, 'value: ', v)
#index: a value: 1
#index: b value: 2
#index: c value: 3
#index: d value: 4
for i, v in s.iteritems():
print('index: ', i,
有时候我们想要的数据合并结果是数据的轴向连接，在pandas中这可以通过concat来实现。操作的对象通常是Series。
Ipython中的交互代码如下：
In [17]: from pandas import Series,DataFrame
In [18]: series1 = Series(range(2),index = ['a','b'])
In [19]: series2 = Series(range(3),index = ['c','d','e'])
In [20]: seri
如下所示：
In [3]: import pandas as pd
In [4]: a = pd.Series([1,2,3])
In [5]: b = pd.Series([2,3,4])
In [6]: c = pd.DataFrame([a,b])
In [7]: c
Out[7]:
0 1 2
0 1 2 3
1 2 3 4
不过pandas直接用列表生成dataframe只能按行生成，如果是字典可以按列生成，比如：
In [8]: c = pd.DataFrame({'a':a
