三、圖表的樣式參數

 

 

 

In [1]:

"""
linestyle、style、color、marker
"""

In [1]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

In [4]:

# linestyle

plt.plot([i**2 for i in range(100)],linestyle = '-.')
# '-'       solid line style
# '--'      dashed line style
# '-.'      dash-dot line style
# ':'       dotted line style

Out[4]:

[<matplotlib.lines.Line2D at 0x1a99447e208>]

 

In [7]:

# marker參數

s = pd.Series(np.random.randn(100).cumsum())
s.plot(linestyle = '--',marker = '*')
# '.'       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
# '|'       vline marker
# '_'       hline marker

Out[7]:

<matplotlib.axes._subplots.AxesSubplot at 0x1a9945c1cc0>

 

In [11]:

# color參數

plt.hist(np.random.randn(100),color = 'g',alpha = 0.8)
# alpha：0-1，透明度
# 經常使用顏色簡寫：red-r, green-g, black-k, blue-b, yellow-y

df = pd.DataFrame(np.random.randn(1000, 4),columns=list('ABCD'))
df = df.cumsum()
# df.plot(style = '--.',alpha = 0.8,colormap = 'Greys')
df.plot(style = '--.',alpha = 0.8,colormap = 'Greys_r')  # 反向
# colormap：顏色板，包括：
# Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r,
# Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, 
# PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, 
# RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, 
# YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, 
# cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r,
# gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, 
# gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, 
# nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spectral, 
# spectral_r ,spring, spring_r, summer, summer_r, terrain, terrain_r, viridis, viridis_r, winter, winter_r

# 其餘參數見「顏色參數.docx」 

Out[11]:

<matplotlib.axes._subplots.AxesSubplot at 0x1a995847f28>

 

 

In [14]:

# style參數，能夠包含linestyle，marker，color

ts = pd.Series(np.random.randn(1000).cumsum(), index=pd.date_range('1/1/2000', periods=1000))
ts.plot(style = '--g.',grid = True)
# style → 風格字符串，這裏包括了linestyle（-），marker（.），color（g）

Out[14]:

<matplotlib.axes._subplots.AxesSubplot at 0x1a9959b5438>

 

In [2]:

# 總體風格樣式
import matplotlib.style as psl
print(plt.style.available)
# 查看樣式列表
psl.use('dark_background') # 
ts = pd.Series(np.random.randn(1000).cumsum(), index=pd.date_range('1/1/2000', periods=1000))
ts.plot(style = '--g.',grid = True,figsize=(10,6))
# 一旦選用樣式後，全部圖表都會有樣式，重啓後才能關掉

 

['bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark-palette', 'seaborn-dark', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'seaborn', 'Solarize_Light2', 'tableau-colorblind10', '_classic_test']

Out[2]:

<matplotlib.axes._subplots.AxesSubplot at 0x1a8692558d0>

 

In [ ]: