如何在python中直观地表示来自github(我的存储库)的csv？

Question

过去两个小时，我一直在google工作，试图让我的代码能够直观地表示数据。问题是当我读取文件时，它们不是csv的，我也不太确定如何将它们转换回csv。然而，我尝试的任何东西都不可能使数据被可视化地表示出来。另一个主要问题是python认为所有的对象都是对象，所以它不会让我将它们转换为float或int。请帮帮忙。

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import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
headers = ['Order ID', 'Product', 'Quantity Ordered', 'Price Each', 'Order Date', 'Purchase Address']
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_January_2019.csv'
January = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_February_2019.csv'
February = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_March_2019.csv'
March = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_April_2019.csv'
April = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_May_2019.csv'
May = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_June_2019.csv'
June = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_July_2019.csv'
July = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_August_2019.csv'
August = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_September_2019.csv'
September = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_October_2019.csv'
October = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_November_2019.csv'
November = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_December_2019.csv'
December = pd.read_csv(url)

January.head()
January.dtypes

January['Price Each'] = January['Price Each'].astype(float)

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Answer 1

我想出来了，伙计们：

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import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
import csv
headers = ['Order ID', 'Product', 'Quantity Ordered', 'Price Each', 'Order Date', 'Purchase Address']
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_January_2019.csv'
January = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_February_2019.csv'
February = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_March_2019.csv'
March = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_April_2019.csv'
April = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_May_2019.csv'
May = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_June_2019.csv'
June = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_July_2019.csv'
July = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_August_2019.csv'
August = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_September_2019.csv'
September = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_October_2019.csv'
October = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_November_2019.csv'
November = pd.read_csv(url, names=headers)
url = 'https://raw.githubusercontent.com/cshort2112/Sample-data/main/Sales_December_2019.csv'
December = pd.read_csv(url)

January.columns
January = January.to_csv('January.csv')
January

x = []
y = []
  
with open('January.csv') as csvfile:
    plots = csv.reader(csvfile, delimiter = ',')
      
    for row in plots:
        x.append(row[1])
        y.append(row[2])
  
plt.bar(x, y, color = 'g', width = 0.72, label = "test")
plt.xlabel('Product')
plt.ylabel('Quantity')
plt.title('Qty by product')
plt.legend()
plt.show()

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