Python数据分析-数据可视化(二)

Python数据分析-数据可视化(二)

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文章目录

前言Matplotlib 折线图格式调整

标签线条颜色线条形状折点样式线条透明度

前言

看到有些论文插图十分简洁美观，于是便摸索一下如何美化一下折线图绘图。本文将在前文Python数据分析-数据可视化的基础上，介绍折线图格式的调整。

本文使用的画图工具为matplotlib，相关API可访问python matplotlib文档。

Matplotlib 折线图格式调整

首先，贴一下文档中折线图绘制的附加参数表：

PropertyDescriptionagg_filtera filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) arrayalphascalar or Noneanimatedboolantialiased or aaboolclip_boxBboxclip_onboolclip_pathPatch or (Path, Transform) or Nonecolor or ccolordash_capstyleCapStyle or {‘butt’, ‘projecting’, ‘round’}dash_joinstyleJoinStyle or {‘miter’, ‘round’, ‘bevel’}dashessequence of floats (on/off ink in points) or (None, None)data(2, N) array or two 1D arraysdrawstyle or ds{‘default’, ‘steps’, ‘steps-pre’, ‘steps-mid’, ‘steps-post’}, default: ‘default’figureFigurefillstyle{‘full’, ‘left’, ‘right’, ‘bottom’, ‘top’, ‘none’}gidstrin_layoutboollabelobjectlinestyle or ls{’-’, ‘–’, ‘-.’, ‘:’, ‘’, (offset, on-off-seq), …}linewidth or lwfloatmarkermarker style string, Path or MarkerStylemarkeredgecolor or meccolormarkeredgewidth or mewfloatmarkerfacecolor or mfccolormarkerfacecoloralt or mfcaltcolormarkersize or msfloatmarkeveryNone or int or (int, int) or slice or list[int] or float or (float, float) or list[bool]path_effectsAbstractPathEffectpickerfloat or callable[[Artist, Event], tuple[bool, dict]]pickradiusfloatrasterizedboolsketch_params(scale: float, length: float, randomness: float)snapbool or Nonesolid_capstyleCapStyle or {‘butt’, ‘projecting’, ‘round’}solid_joinstyleJoinStyle or {‘miter’, ‘round’, ‘bevel’}transformunknownurlstrvisibleboolxdata1D arrayydata1D arrayzorderfloat

接下来，我将挑选几个常用的附加参数介绍使用方式与效果。

标签

附加参数名：label功能：为绘制曲线命名，该名称会在图例显示使用方式：plt.plot(x,y,label=‘example’)

import random

import matplotlib.pyplot as plt

x = range(10)
y = [random.random() for _ in range(10)]

plt.figure()
plt.plot(x, y, label='example')
plt.legend()
plt.show()

线条颜色

附加参数名：color功能：选择绘制线条的颜色使用方式：plt.plot(x,y,color=‘r’)颜色选取方式分为三种：

用全名或简称 ，如blue或b16进制 ，如FF00FF(r, g, b) 或 (r, g, b, a)，如（1,0,1,1） ，其中 r g b a 取均为[0, 1]之间，[0, 1]之间的浮点数的字符串形式，表示灰度值。0表示黑色，1表示白色

import random

import matplotlib.pyplot as plt

x = range(10)
y = [random.random() for _ in range(10)]
y2 = [random.random() for _ in range(10)]
y3 = [random.random() for _ in range(10)]
y4 = [random.random() for _ in range(10)]

plt.figure()
plt.plot(x, y, label='example1', color='blue')
plt.plot(x, y2, label='example2', color='r')
plt.plot(x, y3, label='example3', color='#00FFFF')
plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6))
plt.legend()
plt.show()

线条形状

附加参数名：linestyle(或ls)功能：选择绘制线条的形状使用方式：plt.plot(x,y,linestyle=’:’)或者plt.plot(x,y,ls=’:’)常用形状：

- 实线(solid)– 短线(dashed)-. 短点相间线(dashdot)： 虚点线(dotted)‘’, ’ ', None

import random

import matplotlib.pyplot as plt

x = range(10)
y = [random.random() for _ in range(10)]
y2 = [random.random() for _ in range(10)]
y3 = [random.random() for _ in range(10)]
y4 = [random.random() for _ in range(10)]

plt.figure()
plt.plot(x, y, label='example1', color='blue', linestyle='-')
plt.plot(x, y2, label='example2', color='r', ls='--')
plt.plot(x, y3, label='example3', color='#00FFFF', ls=':')
plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), ls='')
plt.legend()
plt.show()

折点样式

附加参数名：
(1)marker – 折点形状

(2)markeredgecolor 或 mec – 折点外边颜色

(3)markeredgewidth 或 mew – 折点线宽

(4)markerfacecolor 或 mfc --折点实心颜色

(5)markerfacecoloralt 或 mfcalt

(6)markersize 或 ms --折点大小

折点形状选择如下表:

characterdescription'-'solid line style'--'dashed line style'-.'dash-dot line style':'dotted line style'.'point marker','pixel marker'o'circle marker'v'triangle_down marker'^'triangle_up marker'<'triangle_left marker'>'triangle_right marker'1'tri_down marker'2'tri_up marker'3'tri_left marker'4'tri_right marker's'square marker'p'pentagon marker'*'star marker'h'hexagon1 marker'H'hexagon2 marker'+'plus marker'x'x marker'D'diamond marker'd'thin_diamond marker``’'``'_'hline marker

import random

import matplotlib.pyplot as plt

x = range(10)
y = [random.random() for _ in range(10)]
y2 = [random.random() for _ in range(10)]
y3 = [random.random() for _ in range(10)]
y4 = [random.random() for _ in range(10)]

plt.figure()
plt.plot(x, y, label='example1', color='blue', linestyle='-', marker='o')
plt.plot(x, y2, label='example2', color='r', ls='--', marker='1')
plt.plot(x, y3, label='example3', color='#00FFFF', ls=':', marker='2')
plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), marker='3')
plt.legend()
plt.show()

线条透明度

附加参数名：alpha,值在[0,1]之间功能：选择绘制线条的透明度使用方式：plt.plot(x,y,alpha=‘0.9’)

import random

import matplotlib.pyplot as plt

x = range(10)
y = [random.random() for _ in range(10)]
y2 = [random.random() for _ in range(10)]
y3 = [random.random() for _ in range(10)]
y4 = [random.random() for _ in range(10)]

plt.figure()
plt.plot(x, y, label='example1', color='blue', linestyle='-', alpha=0.3)
plt.plot(x, y2, label='example2', color='r', ls='--', alpha=0.1)
plt.plot(x, y3, label='example3', color='#00FFFF', ls=':', alpha=0.5)
plt.plot(x, y4, label='example4', color=(0.4, 0.5, 0.6), ls='')
plt.legend()
plt.show()