英文:
How do I add a column of objects to a dataframe initialized by values from another column?
问题
我有一个从CSV文件中提取的股票符号表格：
Symbol Last Open %Change ATR Earnings Date Sector
153 WHR 138.02 139.21 -2.26% 4.50 01 / 25 消费者自由裁量权
154 WIX 76.86 80.05 -5.33% 4.01 02 / 07 信息技术
155 WM 158.03 158.60 -0.78% 3.10 02 / 01 工业
156 WMT 143.09 144.77 -1.44% 2.58 02 / 07 消费者食品
157 YUM 127.71 128.50 -0.83% 2.17 02 / 07 消费者自由裁量权
我想为每个符号构建一个TaData类的数据对象，并将其添加到一个新列中。
通常，单个符号的TaData构造如下所示：
data = TaData('GOOG')
我想要类似于以下的操作（因为它传递了整个列而不是单独的符号，所以不起作用）：
df = pd.read_csv('watchlist.csv')
df['ta_data'] = TaData(df['Symbol'])
我的唯一选项是使用for循环吗？
英文:
I have a table of stock symbols I'm pulling from a csv file:
Symbol Last Open %Change ATR Earnings Date Sector
153 WHR 138.02 139.21 -2.26% 4.50 01 / 25 Consumer Discretionary
154 WIX 76.86 80.05 -5.33% 4.01 02 / 07 Information Technology
155 WM 158.03 158.60 -0.78% 3.10 02 / 01 Industrials
156 WMT 143.09 144.77 -1.44% 2.58 02 / 07 Consumer Staples
157 YUM 127.71 128.50 -0.83% 2.17 02 / 07 Consumer Discretionary
And I want to construct data objects of class TaData for each symbol and add it to a new column.
TaData for a single symbol is normally constructed like this:
data = TaData('GOOG')
I want something like this (that didn't work since it passed in the whole column instead of individual symbols):
df = pd.read_csv('watchlist.csv')
df['ta_data'] = TaData(df['Symbol'])
Is a for loop my only option?
答案1
得分: 0
我认为pandas的apply函数对你会很有用。在这里找到更多关于pandas的信息。
你可以尝试以下操作：
df['ta_data'] = df['Symbol'].apply(lambda x: TaData(x))
英文:
I think pandas apply function would be useful for you. Find more about pandas here
You can try the following:-
df['ta_data'] = df['Symbol'].apply(lambda x: TaData(x))
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