The concept of matplotlib is not much introduced here.
Small series before also share with you python using matplotlib to achieve the line chart and pie chart effect, interested friends can also click to see, below see Python use Matplotlib to draw histogram method, as follows:
1. Basic Bar Chart
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.bar (range (len data), data) Plt.show ()
The Plt.bar function signature is:
Bar (left, height, width=0.8, Bottom=none, **kwargs)
In fact, the Left,height,width,bottom four parameters determine the position and size of the cylinder. By default, left is the center position of the cylinder (you can change the meaning of the left value by the align parameter), which is:
(left - width / 2, bottom)
To the lower left corner position
(left + width / 2, bottom + height)
To the upper right corner position
For example:
Import Matplotlib.pyplot as Pltdata = [5, 0, 6,, 10]plt.bar ([0.3, 1.7, 4,, 7], data, width=0.6, bottom=[10, 5, 0 , 5]) plt.show ()
2. Set the bar style
(1) Color
The column color can be set by the Facecolor (or FC) keyword parameter, for example:
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.bar (range (len data), data, fc= ' G ') plt.show ()
You can set multiple colors at once by using the Color keyword parameter, for example:
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.bar (range (len (data), data, color= ' RGB ') # or ' color=[' r ', ' G ', ' B '] ' plt.show ()
(2) Stroke
The relevant keyword parameters are:
Edgecolor or EC
LineStyle or LS
LineWidth or LW
For example:
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.bar (len (data), data, ec= ' R ', ls= '--', lw=2) plt.show ()
(3) Filling
The Hatch keyword can be used to set the fill style, with the following values:/, \, |,-, +, X, O, O,., *. For example:
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.bar (len (data), data, ec= ' K ', lw=1, hatch= ' O ') plt.show ( )
3. Set the Tick label
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]labels = [' Tom ', ' Dick ', ' Harry ', ' Slim ', ' Jim ']plt.bar (len (data)), data, Tick_label=labels) Plt.show ()
4. Stacked bar Chart
With the bottom parameter, you can draw a stacked bar chart. For example:
Import NumPy as Npimport matplotlib.pyplot as Pltsize = 5x = Np.arange (size) A = Np.random.random (size) b = np.random.random (size) Plt.bar (x, A, label= ' a ') Plt.bar (x, B, Bottom=a, label= ' B ') plt.legend () plt.show ()
5. Parallel Column Chart
Drawing a parallel histogram is similar to a stacked histogram, which is to draw multiple groups of cylinders, just to control the position and size of each group of cylinders. For example:
Import NumPy as Npimport matplotlib.pyplot as Pltsize = 5x = Np.arange (size) A = Np.random.random (size) b = np.random.random (size) c = np.random.random (size) total_width, n = 0.8, 3width = Total_width/nx = X-(total_width-width)/2plt.bar (x, A, width=width, label= ' a ') Plt.bar (x + width, b, width=width, label= ' B ') Plt.bar (x + 2 * width, C, width=width, label= ' c ') pl T.legend () plt.show ()
6. Bar chart
Use the Barh method to draw a bar chart. For example:
Import Matplotlib.pyplot as Pltdata = [5, +, +, 10]plt.barh (range (len data), data) Plt.show ()
The signature of the Plt.barh method is:
Barh (bottom, Width, height=0.8, Left=none, **kwargs)
You can see similar to the Plt.bar method. Therefore, the drawing of stacked bar charts and parallel bars is similar to the previous, not to repeat.
7. Positive and Negative bar chart
Import NumPy as Npimport matplotlib.pyplot as Plta = Np.array ([5, 5, +, +]) b = Np.array ([[Ten],,]) Plt.bar H (Range (Len (a)), a) Plt.barh (range (len (b)),-B) plt.show ()