Python 在for循环中合并dict

Python 在for循环中合并dict,python,python-2.7,pandas,dataframe,data-manipulation,Python,Python 2.7,Pandas,Dataframe,Data Manipulation,我想使用for循环创建一个新的数据帧 for (name, series) in Quantitative.iteritems(): data = {'Name': pd.Series(name), 'Count': pd.Series(Quantitative[name].size), '% Miss.': pd.Series((sum(Quantitative[name].isnull().values.ravel()) / Quantitative[name].size)

我想使用for循环创建一个新的数据帧

for (name, series) in Quantitative.iteritems():
data = {'Name': pd.Series(name), 'Count': pd.Series(Quantitative[name].size), 
        '% Miss.': pd.Series((sum(Quantitative[name].isnull().values.ravel()) / Quantitative[name].size) * 100), 
        'Card.': pd.Series(Quantitative[name].unique().size), 'Min': pd.Series(Quantitative[name].min()), 
        '1st Qrt.': pd.Series(Quantitative[name].quantile(0.25)), 'Mean': pd.Series(Quantitative[name].mean()), 
        'Median': pd.Series(Quantitative[name].median()), '3rd Qrt.': pd.Series(Quantitative[name].quantile(0.75)), 
        'Max': pd.Series(Quantitative[name].max()), 'Std.': pd.Series(Quantitative[name].std())}
dt = pd.DataFrame(data)
print(pd.DataFrame(dt))

但是,它会创建多个词典。如何将它们合并在一起?

您不需要为dict中的每个项目创建数据帧,然后再合并它们。使用列表理解创建行列表并从中创建数据帧:

rows = [[
    name, series.size, (sum(series.isnull().values.ravel()) / series.size) * 100, 
    series.unique().size, series.min(), series.quantile(0.25), series.mean(), 
    series.median(), series.quantile(0.75), series.max(), series.std()
] for name, series in Quantitative.iteritems()]

dt = pd.DataFrame(
    rows, 
    columns=['Name', 'Count', '% Miss.', 'Card.', 'Min', '1st Qrt.',
             'Mean', 'Median', '3rd Qrt.', 'Max', 'Std.'])
print(dt)

您不需要为dict中的每个项创建数据帧,然后合并它们。使用列表理解创建行列表并从中创建数据帧:

rows = [[
    name, series.size, (sum(series.isnull().values.ravel()) / series.size) * 100, 
    series.unique().size, series.min(), series.quantile(0.25), series.mean(), 
    series.median(), series.quantile(0.75), series.max(), series.std()
] for name, series in Quantitative.iteritems()]

dt = pd.DataFrame(
    rows, 
    columns=['Name', 'Count', '% Miss.', 'Card.', 'Min', '1st Qrt.',
             'Mean', 'Median', '3rd Qrt.', 'Max', 'Std.'])
print(dt)