有条件地迭代并输出数据框和图表答案

【问题标题】：Iterate conditionally and output dataframes and charts有条件地迭代并输出数据框和图表
【发布时间】：2019-07-24 14:36:58
【问题描述】：

我正在尝试为我的每个“vals”输出一个数据框和一个图表。我正在努力拼凑一些 Pythonic 基础知识。

流程：我获取数据框，进行分组，获取总数的百分比...输出表格和图表。但是，我想循环执行此过程，第一次在 Reviewed?=='Yes' 上使用数据帧过滤器，然后在 No 上使用。

data = {'Region': ["US", "US", "US","US"],
        'Gender': ["M","F","F","M"],
        'Reviewed?': ["Yes","Yes","No","No"]}
df = pd.DataFrame(data, columns=['Region','Gender','Reviewed?'])

def func(df):
    vals = ['Yes','No']
    for i in range(len(vals)):
        for x in vals:
            gb[i] = df[df['Reviewed?']==x].groupby(['Gender'])['Region'].count().reset_index()
            total[i] = gb[i]['Region'].sum()
            gb[i]['Percentage'] = (gb[i]['Region'] / total[i])
            gb[i] = gb[i].sort_values(by='Percentage', ascending=False)
            sns.barplot(data=gb[i], x='Region', y='Percentage')
    plt.show()
    return gb[i]

一些错误消息：

ValueError: could not broadcast input array from shape (0,2) into shape (0)

ValueError: cannot copy sequence with size 2 to array axis with dimension 0

ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series

更新这是我想要的蛮力版本。我只是想要一种更高效、更动态的方式来做到这一点。

请注意，我最初并没有明确表示我想将计数保留在最终数据帧中......

import pandas as pd
import seaborn as sns

data = {'Region': ["US", "US", "US","US"],
        'Gender': ["M","F","F","M"],
        'Reviewed?': ["Yes","Yes","No","No"]}
df = pd.DataFrame(data, columns=['Region','Gender','Reviewed?'])

def func(df):
    gb = df[df['Reviewed?']=='No'].groupby(['Gender'])['Region'].count().reset_index()
    total = gb['Region'].sum()
    gb['Percentage'] = (gb['Region'] / total)
    notyetreviewed = gb.sort_values(by='Percentage', ascending=False)
    sns.barplot(data=notyetreviewed, x='Gender', y='Percentage')
    bottom, top = plt.ylim(0,1) 
    plt.show()

    gb = df[df['Reviewed?']=='Yes'].groupby(['Gender'])['Region'].count().reset_index()
    total = gb['Region'].sum()
    gb['Percentage'] = (gb['Region'] / total)
    reviewed = gb.sort_values(by='Percentage', ascending=False)
    bottom, top = plt.ylim(0,1)  
    sns.barplot(data=reviewed, x='Gender', y='Percentage')
    plt.show()

    return notyetreviewed, reviewed
func(df)

【问题讨论】：

您无法在单个代码运行中获得 3 个ValueErrors。它是哪一个？感谢您尝试说明各种尝试
所以，我们这里应该有 2 个图表，每个图表显示 M/F 的 50/50 拆分？
ha，显然你在这方面没有我那么糟糕 :) 在第一个值错误之后，我得到：“在处理上述异常期间，发生了另一个异常：”同样的事情发生在第二个值错误。
是的，我只是为可重现的代码添加了一些虚拟数据。
我试图修复您的缩进，因为它在 func 中缩进了很远，请检查并确保它仍然正确。

标签： python pandas for-loop seaborn

【解决方案1】：

你可以试试这样的：

import pandas as pd

data = {'Region': ["US", "US", "US","US"],
        'Gender': ["M","F","F","M"],
        'Reviewed?': ["Yes","Yes","No","No"]}
df = pd.DataFrame(data, columns=['Region','Gender','Reviewed?'])

for outcome in ['Yes', 'No']:
    filtered = df[df['Reviewed?'].eq(outcome)]['Gender'].value_counts(normalize=True)
    filtered.plot.bar()

在这种情况下，我通过 Reviewed? 结果过滤每个循环上的 DF，然后获取男性和女性的比例值。你的问题提出了一个二元选择，但我想它可以通过for outcome in df['Reviewed?'].unique():

【讨论】：

差不多。如前所述，我正在尝试输出图表和数据框。另外，我喜欢保持计数，这就是我手动计算总数的原因。
@Christopher 我看不到关于保持计数的问题
当然，我没有专门询问计数，但我将其内置到我的代码中。在这一点上，这真的无关紧要。我特别要求的是输出图表和数据框。感谢您对这段代码的帮助。

【解决方案2】：

这是一个边际改进。很高兴看到一个更 Pythonic 的解决方案，它不需要我将 'Reviewed?' 硬编码到函数调用中......

import pandas as pd
import seaborn as sns

data = {'Region': ["US", "US", "US","US"],
        'Gender': ["M","F","F","M"],
        'Reviewed?': ["Yes","Yes","No","No"]}
df = pd.DataFrame(data, columns=['Region','Gender','Reviewed?'])

def func(df,group,reviewed):
    df = df[df['Reviewed?'].isin(reviewed)].groupby([group])['Region'].count().reset_index()
    df['Percentage'] = df['Region'] / df['Region'].sum()
    sns.barplot(data=df, x='Gender', y='Percentage')
    bottom, top = plt.ylim(0,1)
    plt.show()
    return df

df1 = func(df,'Gender',['Yes'])
df1 = func(df,'Gender',['No'])

【讨论】：