我是python的新手,因为我通常在R中编写脚本,因此我正在学习如何适应Pandas数据帧和细微差别。
我有两个dicts列表,我变成了数据帧,因为我认为以这种格式更容易使用。
df1= [{u'test': u'SAT Math', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': 404}, {u'test': u'SAT Verbal', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': 355}, {u'test': u'SAT Writing', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': 363}, {u'test': u'SAT Composite', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': 1122}, {u'test': u'ACT Math', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': None}, {u'test': u'ACT English', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': None}, {u'test': u'ACT Reading', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': None}, {u'test': u'ACT Science', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': None}, {u'test': u'ACT Composite', u'25th_percentile': None, u'75th_percentile': None, u'50th_percentile': None, u'mean': None}]
df2 = [{u'test': u'SAT Composite', u'mean': 1981}, {u'test': u'ACT Composite', u'mean': 29.6}]
然后我将这些作为数据帧:
df1new = DataFrame(df1, columns=['test', '25th_percentile', 'mean', '50th_percentile','75th_percentile'])
df2new = DataFrame(df2)
现在,如果'test'==“ACT Composite”并且'mean'为None
,我想替换df1new中'mean'列的内容我尝试使用combine_first方法,但我相信这需要对数据帧进行更类似的索引。 我也尝试过:
if df1new['test'] == "ACT Composite" and df1new['mean'] == None:
df1new['mean'] == df2new['mean']
以及.replace()变体。
任何建议都将不胜感激! 先感谢您!
答案 0 :(得分:1)
也许这个:
idx = (df1new.test == 'ACT Composite') & df1new['mean'].isnull()
df1new['mean'][idx] = df2new['mean'][1]
我在那里添加了[1]
,因为我认为这就是你想要的,mean
对应ACT Composite
中的df2new
。它也可以写成
df1new['mean'][idx] = df2new['mean'][df2new.test == 'ACT Composite']