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社区首页 >专栏 >在jupyter实现数据的可视化

在jupyter实现数据的可视化

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双面人
发布2019-07-15 15:54:28
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发布2019-07-15 15:54:28
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文章被收录于专栏:热爱IT热爱IT

import pandas as pd

import numpy as np

import matplotlib

import matplotlib.pyplot as plt

%matplotlib inline

df=pd.read_csv('D:\order.csv',encoding="gbk")   #读取数据 df.head(100) 

maoyan_key_factors = df[['title','score']] maoyan_key_factors.head(100)

maoyan_score = maoyan_key_factors[['title', 'score']] groupby_score = maoyan_score.groupby('score') total_groupby_score = groupby_score.count() print(total_groupby_score.rename(columns={'score':'Total'}))

c_score = total_groupby_score.plot(kind='bar') c_score.set_title('Scoring statistics for the top 100 movie of cat eye movie') c_score.set_ylabel('Count')

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我自己的代码如下:

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

df=pd.read_csv('D:\order.csv',encoding="gbk")   #读取数据 df.head(1000)

print(df)这块可以直接把 df打印出来看下结果 maoyan_key_factors = df[['x_id','pay_amount']] maoyan_key_factors.head(100) maoyan_score = maoyan_key_factors[['x_id', 'pay_amount']] groupby_score = maoyan_score.groupby('x_id') total_groupby_score = groupby_score.count() total_groupby_score.rename(columns={'pay_amount':'Total'})

c_score = total_groupby_score.plot(kind='bar') c_score.set_title('Scoring statistics for the top 100 movie of cat eye movie') c_score.set_ylabel('Count')

图表自己都出来了,非常方便。

感叹,这要拿编程语言写半天,还不知道对错!!!!!

备注:csv的文件格式如下:逗号分隔

order_id 订单号

x_id 商 户id

total_amount 订单金额

pay_amount 支付金额

order_id,x_id,total_amount,pay_amount 201906201520073329387129,33,100,1 201906201527017853969512,33,100,1 201906201533561091291430,33,100,1 201906201544143447127726,11,10,1 201906201545406603430237,33,30,30 201906201548385687686104,11,10,1 201906201556535835619315,11,10,1 201906201601409742676819,11,10,1 201906201604045190468329,11,10,1 201906201612152955596419,11,18,1

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