英文:
Adding a column to a dataframe based on another dataframe
问题
我有一个类似这样的数据框
some_info THIS_infoabd set_1def set_1www set_1qqq set_2wws set_22222 set_3
和另一个数据框如下
THIS_info this_algoset_1 algo_1set_2 algo_2set_3 algo_2
我想在第一个数据框中添加一列，基于"THIS_info"的信息，以便我可以得到
some_info THIS_info this_algoabd set_1 algo_1def set_1 algo_1www set_1 algo_1qqq set_2 algo_2wws set_2 algo_22222 set_3 algo_2
有办法实现这个吗？
英文:
I have a dataframe like this
some_info THIS_infoabd set_1def set_1www set_1qqq set_2wws set_22222 set_3
and another dataframe like this
THIS_info this_algoset_1 algo_1set_2 algo_2set_3 algo_2
I want to add a column to the first dataframe, based on the info on "THIS_info" so that I can get
some_info THIS_info this_algoabd set_1 algo_1def set_1 algo_1www set_1 algo_1qqq set_2 algo_2wws set_2 algo_22222 set_3 algo_2
Is there a way to achieve this?
答案1
得分: 2
你可以使用 merge 函数来合并两个数据框（df1 和 df2）：
df1 = pd.merge(df1, df2, how='left', on='THIS_info')print(df1)
输出：
some_info THIS_info this_algoabd set_1 algo_1def set_1 algo_1www set_1 algo_1qqq set_2 algo_2wws set_2 algo_22222 set_3 algo_2
请注意，在这个示例中，参数 how 和 on 是可选的，但在更一般的情况下很有用。
英文:
You can use the merge function to join the two dataframes (df1 and df2):
df1 = pd.merge(df1, df2, how='left', on='THIS_info')print(df1)
Output:
some_info THIS_info this_algoabd set_1 algo_1def set_1 algo_1www set_1 algo_1qqq set_2 algo_2wws set_2 algo_22222 set_3 algo_2
Note that parameters how and on are optional in this example, but are useful in a more general situation.
答案2
得分: 1
你可以使用merge函数，例如
import pandas as pddf_left = pd.DataFrame({"some_info": ["abd", "def", "www", "qqq", "wws", "2222"],"THIS_info": ["set_1", "set_1", "set_1", "set_2", "set_2", "set_3"]})df_right = pd.DataFrame({"THIS_info": ["set_1", "set_2", "set_3"],"this_algo": ["algo_1", "algo_2", "algo_2"]})df = df_left.merge(df_right, on="THIS_info", how="left")print(df)
然后你可以获得输出:
some_info THIS_info this_algo0 abd set_1 algo_11 def set_1 algo_12 www set_1 algo_13 qqq set_2 algo_24 wws set_2 algo_25 2222 set_3 algo_2
英文:
You can use merge function, like
import pandas as pddf_left = pd.DataFrame({"some_info": ["abd", "def", "www", "qqq", "wws", "2222"],"THIS_info": ["set_1", "set_1", "set_1", "set_2", "set_2", "set_3"]})df_right = pd.DataFrame({"THIS_info": ["set_1", "set_2", "set_3"],"this_algo": ["algo_1", "algo_2", "algo_2"]})df = df_left.merge(df_right, on="THIS_info", how="left")print(df)
Then you can get output:
some_info THIS_info this_algo0 abd set_1 algo_11 def set_1 algo_12 www set_1 algo_13 qqq set_2 algo_24 wws set_2 algo_25 2222 set_3 algo_2
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