如何使用数据框中的特定行和列在Panda Python中创建直方图 [英] How to create Histograms in Panda Python Using Specific Rows and Columns in Data Frame

问题描述

我在图片中具有以下数据框，我想拍摄一个直方图，以显示任意一年（例如2010年）世界上所有国家的分布情况。

I have the following data frame in the picture, i want to take a Plot a histogram to show the distribution of all countries in the world for any given year (e.g. 2010).

以下是我的代码表在以下清洁代码之后生成的内容：

Following is my code table generates after the following code of cleaning:

dataSheet = pd.read_excel("http://api.worldbank.org/v2/en/indicator/EN.ATM.CO2E.PC?downloadformat=excel",sheetname="Data")
dataSheet = dataSheet.transpose()
dataSheet = dataSheet.drop(dataSheet.columns[[0,1]], axis=1) ;
dataSheet = dataSheet.drop(['World Development Indicators', 'Unnamed: 2','Unnamed: 3'])

推荐答案

某年（例如2010年）所有国家的直方图​​，我将执行以下操作。在您的代码之后：

In order to plot a histogram of all countries for any given year (e.g. 2010), I would do the following. After your code:

dataSheet = pd.read_excel("http://api.worldbank.org/v2/en/indicator/EN.ATM.CO2E.PC?    downloadformat=excel",sheetname="Data")
dataSheet = dataSheet.transpose()
dataSheet = dataSheet.drop(dataSheet.columns[[0,1]], axis=1)
dataSheet = dataSheet.drop(['World Development Indicators', 'Unnamed: 2','Unnamed: 3'])

我将通过将实际的国家/地区名称分配为列名来重新组织列名：

I would reorganise the column names, by assigning the actual country names as column names:

dataSheet.columns = dataSheet.iloc[1] # here I'm assigning the column names
dataSheet = dataSheet.reindex(dataSheet.index.drop('Data Source')) # here I'm re-indexing and getting rid of the duplicate row

然后我将再次转置数据帧（为了安全起见，我将其分配给新变量）：

Then I would transpose the data frame again (to be safe I'm assigning it to a new variable):

df = dataSheet.transpose()

然后我将执行与分配之前相同的操作新的列名，因此我们得到了一个不错的数据框（尽管仍然不是最佳），并以国家/地区名称作为索引。

And then I'd do the same as I did before with assigning new column names, so we get a decent data frame (although still not optimal) with country names as index.

df.columns = df.iloc[0]
df = df.reindex(df.index.drop('Country Name'))

现在您终于可以绘制直方图，例如2010年：

Now you can finally plot the histogram for e.g. year 2010:

import matplotlib.pyplot as plt
df[2010].plot(kind='bar', figsize=[30,10])

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