在jupyter實現數據的可視化

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")   #讀取數據
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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我本身的代碼以下：

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")   #讀取數據
df.head(1000)

print(df)這塊能夠直接把 df打印出來看下結果
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')

圖表本身都出來了，很是方便。

感嘆，這要拿編程語言寫半天，還不知道對錯！！！！！

備註：csv的文件格式以下：逗號分隔

order_id 訂單號

x_id 商 戶id

total_amount 訂單金額

pay_amount 支付金額

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