Python：如何使用 2 个数据帧创建新的数据帧，这两个数据帧之一的数据必须被其他列名替换

Question

All I want to do is to create a stocks' decile frame by industry factor model.

So far, I've made a decile frame based on industry's factor named as zongmok

And a frame called inds that shows information about which industry does stock belong to.

The problem is that how to create a new data frame to show each stock's decile based on industry factor at every index time. (The new data frame is called df, and I've tried to use squared for loop, But It was too slow to complete the whole task.)

Here's the code I've tried:

for i in notebook.tqdm(range(len(df))):
    for j in notebook.tqdm(range(len(df.columns))):
        try:
            df[df.columns[j]].loc[df.index[i]] = zongmok[inds.loc[df.index][inds == zongmok.columns[j]].dropna(axis=1)[inds[inds == zongmok.columns[j]].dropna(axis=1).columns[j]].loc[df.index[i]]].loc[df.index[i]]
        except Exception:
            pass
        else:
            pass

Answer 1

By using merge() it will be easier for you to join two dataframe together without all of these iterations;

Example:

I've dataframe called prod_df and I want to merge it with another dataframe called market_df . This's how it goes:

Dataframe of prod_df :

Dataframe of market_df :

**Code Syntax for merging them using Inner Join :

# Lets join the two dataframe depending on `prod_df
second_merge_df = pd.merge(prod_df, market_df, how='inner', on='Prod_id')
second_merge_df.sort_values(by='Prod_id', ascending=True)

OUTPUT