Matplotlib之条形图与散点图

一、前言

上一篇Matplotlib中的折线图与子图简单介绍之后,接下来介绍一下条形图与散点图,主要还是以代码形式来介绍会直接点。

二、柱形图

【1】代码示例一:

import matplotlib.pyplot as plt
import pandas as pd
from numpy import arange
# 根据文件获取数据
reviews=pd.read_csv('C:\\Users\\Lenovo\\Desktop\\python\\pandaTest.csv')
num_cols = ['first','second','three','four','five','seven','eight']
norm_reviews=reviews[num_cols]
# 获取每条柱形的值
bar_heights = norm_reviews.ix[0,num_cols].values
# print(bar_heights)
# 获取每条柱离原点的距离
bar_positions=arange(7)+1
# print(bar_positions)
fig,ax=plt.subplots()
ax.bar(bar_positions,bar_heights,0.2)
plt.show()

结果图如下所示:
在这里插入图片描述
【2】代码示例二:

import matplotlib.pyplot as plt
import pandas as pd
from numpy import arange
# 根据文件获取数据
reviews=pd.read_csv('C:\\Users\\Lenovo\\Desktop\\python\\pandaTest.csv')
num_cols = ['first','second','three','four','five','seven','eight']
norm_reviews=reviews[num_cols]
# 获取每条柱形的值
bar_heights = norm_reviews.ix[0,num_cols].values
print(bar_heights)
# 获取每条柱离原点的距离
bar_positions=arange(7)+1
print(bar_positions)
fig,ax=plt.subplots()
ax.bar(bar_positions,bar_heights,0.2)

tick_posotions=range(1,8)

ax.set_xticks(tick_posotions)
ax.set_xticklabels(cols)
ax.set_ylabel('yLabel')
ax.set_xlabel('xLabel')
ax.set_title('hello world')

plt.show()

结果图如下所示:
在这里插入图片描述

三、散点图

【1】代码示例一:

import matplotlib.pyplot as plt
import pandas as pd
from numpy import arange
reviews=pd.read_csv('C:\\Users\\Lenovo\\Desktop\\python\\pandaTest.csv')

num_cols = ['first','second','three','four','five','seven','eight']
norm_reviews=reviews[num_cols]
bar_heights = norm_reviews.ix[0,num_cols].values
print(bar_heights)

bar_positions=arange(7)+1
fig,ax=plt.subplots()
ax.scatter(norm_reviews['first'],norm_reviews['second'])
ax.set_xlabel('xLabel')
ax.set_ylabel('yLabel')
ax.set_title('hello world')
plt.show()

结果图如下所示:
在这里插入图片描述

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转载自blog.csdn.net/weixin_42146366/article/details/90812335