A small example collection xlrd,matplotlib,numpy,scipy use method (import data from Excel)

The reason for a paper recently, to get some data from Excel to draw, but the resulting figure is a bitmap, not too good to insert into the paper, so decided to use Python paint to solve this problem (not using MATLAB because it is the picture is not good-looking)

The first library to use is the XLRD library, which functions from reading Excel data

#对应的所有例子中使用的方法贴到了文章最后, easy to find
import xlrd
#首先实例化一个book对象 book
= Xlrd.open_workbook ("One Excel Address")
# Then get all the sheet names for this book and return a list
sheetname = Book.sheet_names ()
#获取sheet类的一个对象, that is, if you know the name of each sheet, You can instantiate it directly with sheet's name
Sheet1 = book.sheet_by_name (sheetname[0))
#然后我们去获得这个对象的列的数据, For example, the following line obtains the first 40 data of the Sheet1, the first column of the sheet, in the form of a list
Data_col = sheet1.col_values (0) [0:40]

#到目前为止, We've achieved the goal of getting the data.

And then use the Library Numpy,matplotlib Library

Import NumPy as NP
import Matplotlib,pyplot as Plt
#我们利用上面得到的数据进行处理
#生成一个X轴array
x = Np.arange (1,len ( Data_col) +1,1
#利用导入的Excel表格获得的list类型的数据赋值给y
y = Np.array (data_col)
#绘制x, y image
Plt.plot (X,y,label = "Test", FontSize =
#添加横坐标
plt.xlabel ("Time")
Add ordinate
plt.ylabel ("displacement")
# Add Legend
plt.legend (loc = 0)
plt.show ()

Period, the SciPy library is used to smooth the curve

From scipy.interpolate import spline
#使用方法如下
xnew = Np.linspace (X.min (), X.max (), +)
ynew = spline (x,y , xnew)
#现在就可以使用如下方式画出smooth的图
plt.plot (xnew,ynew)

how to achieve the drawing of a canvas with multiple graphs and a double y-axis diagram

#实现一个画布多个图的方法
#plt. Subplot (Rows,cols,num), use this before each diagram you draw, and then modify the third parameter representing the position of each diagram
Plt.subplot (2,2,1)

# method to implement double y-axis
Plt.twinx ()

attach a complete example of code written by nonstandard

Import Matplotlib.pyplot as PLT import numpy as NP import xlrd from scipy.interpolate import spline book = Xlrd.open_work Book ("National Network data-displacement-acceleration. xls") sheet = book.sheet_names () [0:4] # Print (sheet) Sheet_con = [] for data in Sheet:sheet_con.app
    End (Book.sheet_by_name (data)) # Print (sheet_con) i = 0 for all_data in sheet_con:y1 = all_data.col_values (0) [1:40] y2 = all_data.col_values (1) [1:40] x = Np.arange (1,len (y1) +1,1) i = i + 1 xnew = Np.linspace (X.min (), X.max (), Y1 = spline (x,y1,xnew) y2 = spline (x,y2,xnew) Plt.subplot (2,2,i) plt.plot (xnew,y1, "B", linewidth = 2,l Abel = "Acceleration") plt.legend (loc = 2) Plt.xlabel ("time/(0.1s)") If i = = 1 or i = = 3:plt.ylabel (" Acceleration of x/(g) ") Else:plt.ylabel (" Acceleration of z/(g) ") Plt.twinx () Plt.plot (Xnew,y2," r--", L Inewidth = 2,label = "Displacement") plt.legend (loc = 3) If i = = 1 or i = = 2:plt.ylabel ("Displacement of Label 1/(MM) ") Else:
        Plt.ylabel ("Displacement of label 2/(mm)") # Plt.title ("Relationship between acceleration and displacement") plt . Show ()

Xlrd About method Introduction

#获取这个sheet_name对应的sheet对象 Sheet_by_name (Sheet_name) [#] Sheet_name name of sheet required Returns:an Obje CT of the Sheet class #获取book对象中所有的sheet的名字 (return list form) Sheet_names () [#] Returns:a list of the names of the sheets

In the book.

#获取book中所有sheet的地址 sheets () [#] Returns:a list of all sheets in the book.

Col_slice (Colx, start_rowx=0, End_rowx=none) [#] Returns a slice of the Cell objects in the given column.

Col_types (Colx, start_rowx=0, End_rowx=none) [#] Returns a slice of the types of the cells in the given column.
    #sheet对象的一个方法, get the Colx column of this sheet object, from start_rowx to End_rowx list of all data Col_values (Colx, start_rowx=0, End_rowx=none) [#]

Returns a slice of the values of the cells in the given column.

Name [#] name of sheet. #获取sheet对象中column的列数 Ncols [#] Number of columns in sheet.

A column index is in range (Thesheet.ncols). #获取sheet对象中row行数 nrows [#] number of rows in sheet.

A row index is in range (thesheet.nrows). Row (ROWX) [#]
    Returns a sequence the Cell objects in the given row. row_label_ranges [#] List of address ranges of cells containing row labels. 
    For more details, col_label_ranges above. --New in version 0.6.0 Row_slice (rowx, start_colx=0, End_colx=none) [#] Returns a slice of the Cell objects in the G

Iven row.

Row_types (Rowx, start_colx=0, End_colx=none) [#] Returns a slice of the types of the cells in the given row.
Row_values (Rowx, start_colx=0, End_colx=none) [#] Returns a slice of the values of the cells in the given row. Above excerpted from http://www.lexicon.net/sjmachin/xlrd.html

This is a brief introduction to the NumPy and Matplotlib reference method

#获得一个初值, end value, step length array
numpy.arange ([Start,]stop, [step,]) return
    evenly spaced values within a given interval.< c3/> #传入一个list直接生成array
Numpy.array (object, Dtype=none, Copy=true, order= ' K ', Subok=false, ndmin=0)
    return Array.
    Object:array_like--an array, any object exposing the array interface, a object whose __array__ method returns an array, or any (nested) sequence.

#label指的是次线条的标签, Linewieth is the line width, fontsize is the font size
plot ([1,2,3], [1,2,3], ' go-', label= ' lines 1 ', linewidth=2,fontsize =

#xlabel设定
Matplotlib.pyplot.xlabel (S, *args, **kwargs) Set the
    x axis label of the current axis.
    Default Override is:
    override = {
        ' fontsize '            : ' small ', '
        verticalalignment '   : ' Top ',
        ' HorizontalAlignment ': ' Center '
        }

#legend设定, location's number is represented by the position
plt.legend (loc = 0)

Location String	Location Code
' Best '	0
' upper right '	1
' upper left '	2
' lower left '	3
' lower right '	4
"right"	5
' center left '	6
' center right '	7
' Lower center '	8
' Upper Center '	9
' center '	ten

#生成一个初值终值为范围, a sample of Numpy.linspace (Start, Stop, num=50, Endpoint=true, Retstep=false, Dtype=none) return EV with NUM as the uniform interval point
    Enly spaced numbers over a specified interval.
    Returns num evenly spaced (evenly spaced) samples, calculated over the interval [start, stop].

The endpoint of the interval can optionally be excluded.
    #一画布多图片 Matplotlib.pyplot.subplot (*args, **kwargs) return a subplot axes positioned by the given grid definition. Typical call Signature: #画布中, the distribution position of the image subplot (nrows, Ncols, Plot_number) where nrows and Ncols are to.  Ionally split the figure into nrows * Ncols sub-axes, and plot_number are used to identify the particular subplot The function is to create within the notional grid.
    Plot_number starts at 1, increments across rows A and has a maximum of nrows * ncols. In the "case" nrows, Ncols and Plot_number are all less than, a convenience exists, such that the a 3 digit number C An is given instead, where the hundreds RepresenT nrows, the Tens represent ncols and the units represent #双Y轴方法的实现 Plot_number (Matplotlib.pyplot.twinx) make A second axes that shares the x-axis. The new axes would overlay ax (or the current axes if Ax is None). The ticks for AX2 would be placed on the right and the AX2 instance is returned.

a method of scipy

Scipy.interpolate.spline (*args, **kwds) [source]
interpolate a curve in new points using a spline fit
Parameters: 
    XK, Yk:array_like
    The X and Y values that define the curve.
    Xnew:array_like the
    x values where spline should estimate the Y values.
Address: Https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html#spline-interpolation