在两个不同的pandas Dataframe之间循环和匹配字符串

Question

I have two different dataframes df and df2, and i want to loop through each row of df in search of certain matches within specific rows in df2 and return a txt file for each match.

df=

 name Tec Location jhon js sr nz mark python ssr us alan java jr mx 

df2=

 company job Country Index company a js jr uk 1 company b python ssr us 2 company c java jr mx 3 

So far i've been doing the following:

 for index, row in df.iterrows(): for indexb, rowb in df2.iterrows(): if str(row.Tec) in str(rowb.job) and str(row.Location) in rowb.Country: print ('Match with ' + str(rowb.company)) sys.stdout= open(r'path\\to\\file\\%s.txt'%(row['name']+ str(rowb.Index),), 'w') else: pass 

I keep getting text files with wrong matches or with the first row from df2 repeated within all output txt files. I want to compare Tec against job and Location against country. So for example, an output for this case would be: mark 2.txt , where the file contains the text "Match with company b"

Any idea ?

Answer 1

Iterating rows is not the preferred way of working with Pandas DataFrames.

You might want to try joining df and df2. Then apply a filter to keep the rows you want to save into csv.

df = pd.DataFrame([['jhon', 'js sr', 'nz'], ['mark', 'python ssr', 'us'], ['alan', 'java jr', 'mx']], columns=['name', 'Tec', 'Location'])
df2 = pd.DataFrame([['company a', 'js jr', 'uk'], ['company b', 'python ssr', 'us'], ['company c', 'java jr', 'mx']], columns=['company', 'job', 'Country'])
# Merge the two dataframes
df3 = df.merge(df2, how='right', left_on=['Tec', 'Location'], right_on=['job', 'Country'])
df3 = df3[df3['name'].notnull()]
df3['name'].to_csv('output.csv')