pandas: union of two data frames












6















Say I have two data frames:



df1:



  A

0 a

1 b


df2:



  A

0 a

1 c


I want the result to be the union of the two frames with an extra column showing the source data frame that the row belongs to. In case of duplicates, duplicates should be removed and the respective extra column should show both sources:



  A  B

0 a  df1, df2

1 b  df1

2 c  df2


I can get the concatenated data frame (df3) without duplicates as follows: 



import pandas as pd

df3=pd.concat([df1,df2],ignore_index=True).drop_duplicates().reset_index(drop=True)


I can't think of/find a method to have control over what element goes where. How can I add the extra column?



Thank you very much for any tips.






python pandas dataframe concatenation







share|improve this question







New contributor




Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

























    6















    Say I have two data frames:



    df1:



      A
    
0 a
    
1 b


    df2:



      A
    
0 a
    
1 c


    I want the result to be the union of the two frames with an extra column showing the source data frame that the row belongs to. In case of duplicates, duplicates should be removed and the respective extra column should show both sources:



      A  B
    
0 a  df1, df2
    
1 b  df1
    
2 c  df2


    I can get the concatenated data frame (df3) without duplicates as follows: 



    import pandas as pd
    
df3=pd.concat([df1,df2],ignore_index=True).drop_duplicates().reset_index(drop=True)


    I can't think of/find a method to have control over what element goes where. How can I add the extra column?



    Thank you very much for any tips.






    python pandas dataframe concatenation







    share|improve this question







    New contributor




    Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.























      6












      6








      6








      Say I have two data frames:



      df1:



        A
      
0 a
      
1 b


      df2:



        A
      
0 a
      
1 c


      I want the result to be the union of the two frames with an extra column showing the source data frame that the row belongs to. In case of duplicates, duplicates should be removed and the respective extra column should show both sources:



        A  B
      
0 a  df1, df2
      
1 b  df1
      
2 c  df2


      I can get the concatenated data frame (df3) without duplicates as follows: 



      import pandas as pd
      
df3=pd.concat([df1,df2],ignore_index=True).drop_duplicates().reset_index(drop=True)


      I can't think of/find a method to have control over what element goes where. How can I add the extra column?



      Thank you very much for any tips.






      python pandas dataframe concatenation







      share|improve this question







      New contributor




      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.












      Say I have two data frames:



      df1:



        A
      
0 a
      
1 b


      df2:



        A
      
0 a
      
1 c


      I want the result to be the union of the two frames with an extra column showing the source data frame that the row belongs to. In case of duplicates, duplicates should be removed and the respective extra column should show both sources:



        A  B
      
0 a  df1, df2
      
1 b  df1
      
2 c  df2


      I can get the concatenated data frame (df3) without duplicates as follows: 



      import pandas as pd
      
df3=pd.concat([df1,df2],ignore_index=True).drop_duplicates().reset_index(drop=True)


      I can't think of/find a method to have control over what element goes where. How can I add the extra column?



      Thank you very much for any tips.






      python pandas dataframe concatenation




      python pandas dataframe concatenation






      share|improve this question







      New contributor




      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question







      New contributor




      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




      share|improve this question






      New contributor




      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked 2 hours ago









      Leon RaiLeon Rai

      455




      455




      New contributor




      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.





      New contributor





      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      Leon Rai is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.
























          3 Answers
          3






          active

          oldest

          votes


















          8














          Merge with an indicator argument, and remap the result:



          m = {'left_only': 'df1', 'right_only': 'df2', 'both': 'df1, df2'}
          

          
result = df1.merge(df2, on=['A'], how='outer', indicator='B')
          
result['B'] = result['B'].map(m)
          

          
result
          
   A         B
          
0  a  df1, df2
          
1  b       df1
          
2  c       df2





          share|improve this answer
























          • Nice and succinct!

            – cph_sto
            2 hours ago











          • @cph_sto Thank you! Upvoted back.

            – coldspeed
            2 hours ago






          • 1





            I have learnt a lot from you.

            – cph_sto
            2 hours ago











          • Excellent! Could you add how to do the same for intersection? outer->inner?

            – Leon Rai
            1 hour ago








          • 1





            @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

            – coldspeed
            1 hour ago



















          2














          We use outer join to solve this -



          df1 = pd.DataFrame({'A':['a','b']})
          
df2 = pd.DataFrame({'A':['a','c']})
          
df1['col1']='df1'
          
df2['col2']='df2'
          
df=pd.merge(df1, df2, on=['A'], how="outer").fillna('')
          
df['B']=df['col1']+','+df['col2']
          
df['B'] = df['B'].str.strip(',')
          
df=df[['A','B']]
          
df
          

          
   A        B
          
0  a  df1,df2
          
1  b      df1
          
2  c      df2





          share|improve this answer
























          • thank you for the answer!

            – Leon Rai
            1 hour ago











          • pleasure Leon :)

            – cph_sto
            1 hour ago



















          2














          Use the command below:



          df3 = pd.concat([df1.assign(source='df1'), df2.assign(source='df2')]) 
          
    .groupby('A') 
          
    .aggregate(list) 
          
    .reset_index()


          The result will be:



             A      source
          
0  a  [df1, df2]
          
1  b       [df1]
          
2  c       [df2]


          The assign will add a column named source with value df1 and df2 to your dataframes. groupby command groups rows with same A value to single row. aggregate command describes how to aggregate other columns (source) for each group of rows with same A. I have used list aggregate function so that the source column be the list of values with same A.






          share|improve this answer










          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.





















          • thank you for the answer!

            – Leon Rai
            1 hour ago











          Your Answer






          StackExchange.ifUsing("editor", function () {
          StackExchange.using("externalEditor", function () {
          StackExchange.using("snippets", function () {
          StackExchange.snippets.init();
          });
          });
          }, "code-snippets");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "1"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });






          Leon Rai is a new contributor. Be nice, and check out our Code of Conduct.










          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f54315222%2fpandas-union-of-two-data-frames%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          3 Answers
          3






          active

          oldest

          votes








          3 Answers
          3






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          8














          Merge with an indicator argument, and remap the result:



          m = {'left_only': 'df1', 'right_only': 'df2', 'both': 'df1, df2'}
          

          
result = df1.merge(df2, on=['A'], how='outer', indicator='B')
          
result['B'] = result['B'].map(m)
          

          
result
          
   A         B
          
0  a  df1, df2
          
1  b       df1
          
2  c       df2





          share|improve this answer
























          • Nice and succinct!

            – cph_sto
            2 hours ago











          • @cph_sto Thank you! Upvoted back.

            – coldspeed
            2 hours ago






          • 1





            I have learnt a lot from you.

            – cph_sto
            2 hours ago











          • Excellent! Could you add how to do the same for intersection? outer->inner?

            – Leon Rai
            1 hour ago








          • 1





            @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

            – coldspeed
            1 hour ago
















          8














          Merge with an indicator argument, and remap the result:



          m = {'left_only': 'df1', 'right_only': 'df2', 'both': 'df1, df2'}
          

          
result = df1.merge(df2, on=['A'], how='outer', indicator='B')
          
result['B'] = result['B'].map(m)
          

          
result
          
   A         B
          
0  a  df1, df2
          
1  b       df1
          
2  c       df2





          share|improve this answer
























          • Nice and succinct!

            – cph_sto
            2 hours ago











          • @cph_sto Thank you! Upvoted back.

            – coldspeed
            2 hours ago






          • 1





            I have learnt a lot from you.

            – cph_sto
            2 hours ago











          • Excellent! Could you add how to do the same for intersection? outer->inner?

            – Leon Rai
            1 hour ago








          • 1





            @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

            – coldspeed
            1 hour ago














          8












          8








          8







          Merge with an indicator argument, and remap the result:



          m = {'left_only': 'df1', 'right_only': 'df2', 'both': 'df1, df2'}
          

          
result = df1.merge(df2, on=['A'], how='outer', indicator='B')
          
result['B'] = result['B'].map(m)
          

          
result
          
   A         B
          
0  a  df1, df2
          
1  b       df1
          
2  c       df2





          share|improve this answer













          Merge with an indicator argument, and remap the result:



          m = {'left_only': 'df1', 'right_only': 'df2', 'both': 'df1, df2'}
          

          
result = df1.merge(df2, on=['A'], how='outer', indicator='B')
          
result['B'] = result['B'].map(m)
          

          
result
          
   A         B
          
0  a  df1, df2
          
1  b       df1
          
2  c       df2






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered 2 hours ago









          coldspeedcoldspeed

          126k23126213




          126k23126213













          • Nice and succinct!

            – cph_sto
            2 hours ago











          • @cph_sto Thank you! Upvoted back.

            – coldspeed
            2 hours ago






          • 1





            I have learnt a lot from you.

            – cph_sto
            2 hours ago











          • Excellent! Could you add how to do the same for intersection? outer->inner?

            – Leon Rai
            1 hour ago








          • 1





            @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

            – coldspeed
            1 hour ago



















          • Nice and succinct!

            – cph_sto
            2 hours ago











          • @cph_sto Thank you! Upvoted back.

            – coldspeed
            2 hours ago






          • 1





            I have learnt a lot from you.

            – cph_sto
            2 hours ago











          • Excellent! Could you add how to do the same for intersection? outer->inner?

            – Leon Rai
            1 hour ago








          • 1





            @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

            – coldspeed
            1 hour ago

















          Nice and succinct!

          – cph_sto
          2 hours ago





          Nice and succinct!

          – cph_sto
          2 hours ago













          @cph_sto Thank you! Upvoted back.

          – coldspeed
          2 hours ago





          @cph_sto Thank you! Upvoted back.

          – coldspeed
          2 hours ago




          1




          1





          I have learnt a lot from you.

          – cph_sto
          2 hours ago





          I have learnt a lot from you.

          – cph_sto
          2 hours ago













          Excellent! Could you add how to do the same for intersection? outer->inner?

          – Leon Rai
          1 hour ago







          Excellent! Could you add how to do the same for intersection? outer->inner?

          – Leon Rai
          1 hour ago






          1




          1





          @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

          – coldspeed
          1 hour ago





          @LeonRai df1.merge(df2, on=['A'], how='inner').assign(B='df1, df2') (since intersection implies membership in both)

          – coldspeed
          1 hour ago













          2














          We use outer join to solve this -



          df1 = pd.DataFrame({'A':['a','b']})
          
df2 = pd.DataFrame({'A':['a','c']})
          
df1['col1']='df1'
          
df2['col2']='df2'
          
df=pd.merge(df1, df2, on=['A'], how="outer").fillna('')
          
df['B']=df['col1']+','+df['col2']
          
df['B'] = df['B'].str.strip(',')
          
df=df[['A','B']]
          
df
          

          
   A        B
          
0  a  df1,df2
          
1  b      df1
          
2  c      df2





          share|improve this answer
























          • thank you for the answer!

            – Leon Rai
            1 hour ago











          • pleasure Leon :)

            – cph_sto
            1 hour ago
















          2














          We use outer join to solve this -



          df1 = pd.DataFrame({'A':['a','b']})
          
df2 = pd.DataFrame({'A':['a','c']})
          
df1['col1']='df1'
          
df2['col2']='df2'
          
df=pd.merge(df1, df2, on=['A'], how="outer").fillna('')
          
df['B']=df['col1']+','+df['col2']
          
df['B'] = df['B'].str.strip(',')
          
df=df[['A','B']]
          
df
          

          
   A        B
          
0  a  df1,df2
          
1  b      df1
          
2  c      df2





          share|improve this answer
























          • thank you for the answer!

            – Leon Rai
            1 hour ago











          • pleasure Leon :)

            – cph_sto
            1 hour ago














          2












          2








          2







          We use outer join to solve this -



          df1 = pd.DataFrame({'A':['a','b']})
          
df2 = pd.DataFrame({'A':['a','c']})
          
df1['col1']='df1'
          
df2['col2']='df2'
          
df=pd.merge(df1, df2, on=['A'], how="outer").fillna('')
          
df['B']=df['col1']+','+df['col2']
          
df['B'] = df['B'].str.strip(',')
          
df=df[['A','B']]
          
df
          

          
   A        B
          
0  a  df1,df2
          
1  b      df1
          
2  c      df2





          share|improve this answer













          We use outer join to solve this -



          df1 = pd.DataFrame({'A':['a','b']})
          
df2 = pd.DataFrame({'A':['a','c']})
          
df1['col1']='df1'
          
df2['col2']='df2'
          
df=pd.merge(df1, df2, on=['A'], how="outer").fillna('')
          
df['B']=df['col1']+','+df['col2']
          
df['B'] = df['B'].str.strip(',')
          
df=df[['A','B']]
          
df
          

          
   A        B
          
0  a  df1,df2
          
1  b      df1
          
2  c      df2






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered 2 hours ago









          cph_stocph_sto

          1,519320




          1,519320













          • thank you for the answer!

            – Leon Rai
            1 hour ago











          • pleasure Leon :)

            – cph_sto
            1 hour ago



















          • thank you for the answer!

            – Leon Rai
            1 hour ago











          • pleasure Leon :)

            – cph_sto
            1 hour ago

















          thank you for the answer!

          – Leon Rai
          1 hour ago





          thank you for the answer!

          – Leon Rai
          1 hour ago













          pleasure Leon :)

          – cph_sto
          1 hour ago





          pleasure Leon :)

          – cph_sto
          1 hour ago











          2














          Use the command below:



          df3 = pd.concat([df1.assign(source='df1'), df2.assign(source='df2')]) 
          
    .groupby('A') 
          
    .aggregate(list) 
          
    .reset_index()


          The result will be:



             A      source
          
0  a  [df1, df2]
          
1  b       [df1]
          
2  c       [df2]


          The assign will add a column named source with value df1 and df2 to your dataframes. groupby command groups rows with same A value to single row. aggregate command describes how to aggregate other columns (source) for each group of rows with same A. I have used list aggregate function so that the source column be the list of values with same A.






          share|improve this answer










          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.





















          • thank you for the answer!

            – Leon Rai
            1 hour ago
















          2














          Use the command below:



          df3 = pd.concat([df1.assign(source='df1'), df2.assign(source='df2')]) 
          
    .groupby('A') 
          
    .aggregate(list) 
          
    .reset_index()


          The result will be:



             A      source
          
0  a  [df1, df2]
          
1  b       [df1]
          
2  c       [df2]


          The assign will add a column named source with value df1 and df2 to your dataframes. groupby command groups rows with same A value to single row. aggregate command describes how to aggregate other columns (source) for each group of rows with same A. I have used list aggregate function so that the source column be the list of values with same A.






          share|improve this answer










          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.





















          • thank you for the answer!

            – Leon Rai
            1 hour ago














          2












          2








          2







          Use the command below:



          df3 = pd.concat([df1.assign(source='df1'), df2.assign(source='df2')]) 
          
    .groupby('A') 
          
    .aggregate(list) 
          
    .reset_index()


          The result will be:



             A      source
          
0  a  [df1, df2]
          
1  b       [df1]
          
2  c       [df2]


          The assign will add a column named source with value df1 and df2 to your dataframes. groupby command groups rows with same A value to single row. aggregate command describes how to aggregate other columns (source) for each group of rows with same A. I have used list aggregate function so that the source column be the list of values with same A.






          share|improve this answer










          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.










          Use the command below:



          df3 = pd.concat([df1.assign(source='df1'), df2.assign(source='df2')]) 
          
    .groupby('A') 
          
    .aggregate(list) 
          
    .reset_index()


          The result will be:



             A      source
          
0  a  [df1, df2]
          
1  b       [df1]
          
2  c       [df2]


          The assign will add a column named source with value df1 and df2 to your dataframes. groupby command groups rows with same A value to single row. aggregate command describes how to aggregate other columns (source) for each group of rows with same A. I have used list aggregate function so that the source column be the list of values with same A.







          share|improve this answer










          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.









          share|improve this answer



          share|improve this answer








          edited 2 hours ago





















          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.









          answered 2 hours ago









          Narges AyoubiNarges Ayoubi

          564




          564




          New contributor




          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.





          New contributor





          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          Narges Ayoubi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.













          • thank you for the answer!

            – Leon Rai
            1 hour ago



















          • thank you for the answer!

            – Leon Rai
            1 hour ago

















          thank you for the answer!

          – Leon Rai
          1 hour ago





          thank you for the answer!

          – Leon Rai
          1 hour ago










          Leon Rai is a new contributor. Be nice, and check out our Code of Conduct.










          draft saved

          draft discarded


















          Leon Rai is a new contributor. Be nice, and check out our Code of Conduct.













          Leon Rai is a new contributor. Be nice, and check out our Code of Conduct.












          Leon Rai is a new contributor. Be nice, and check out our Code of Conduct.
















          Thanks for contributing an answer to Stack Overflow!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid …



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f54315222%2fpandas-union-of-two-data-frames%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          -

          Popular posts from this blog

          الفوسفات في المغرب

          Image
          قطار ينقل فوسفات من منطقة خريبكة متجه نحو الدار البيضاء. ديار عمال بمصانع الفوسفات بمدينة آسفي. المحتوى هنا ينقصه الاستشهاد بمصادر. يرجى إيراد مصادر موثوق بها. أي معلومات غير موثقة يمكن التشكيك بها وإزالتها. (أغسطس 2015) الفوسفات في المغرب هو ثالث مصدر عالمي للفوسفات، ويتوفر المغرب على %75 من الاحتياطي العالمي  [بحاجة لمصدر] ويتوزع بنسب متفاوتة بين عدة مناطق أساسية وهي: وادي زم بن جرير بوكراع خريبكة اليوسفية أولاد عبدون كنتور واد الذهب مستقلة. هذه الأخيرة لم تفتح بعد للاستغلال. الصادرات الحامض الفوسفوري P205 تمتص الهند %50 من ا لصادرات الإجمالية آسيا (دون روسيا)%59 أوروبا %30 أمريكا اللاتينية %11 أسمدة صلبة أوروبا 38 % أمريكا اللاتينية %30 آسيا (دون روسيا) 22 % أستراليا 9 % بوابة المغرب هذه بذرة مقالة عن علم الاقتصاد أو موضوع متعلق به بحاجة للتوسيع. شارك في تحريرها. This page is only for reference, If you need detailed information, please check here
          Read more

          Four equal circles intersect: What is the area of the small shaded portion and its height

          Image
          3 $begingroup$ In terms of $R$ which is the radius of all four circles, what is the area of the intersection region of these four equal circles and the height of the marked arrow in the figure? The marked arrow is along the line CD, also the midpoint of all the circles are points A, B, C and D. Looking for a very short intuitive solution. I have checked similar questions on this site for example this and this. geometry circle share | cite | improve this question edited 2 hours ago Abdulhameed asked 2 hours ago ...
          Read more

          جامعة ليفربول

          Image
          جامعة ليفربول University of Liverpool الأسماء السابقة كلية ليفربول الجامعية (1882-1884) جامعة فيكتوريا في ليفربول (1884-1903) معلومات التأسيس 1882 (منذ 137 سنة) الإنتماءات رابطة الجامعات الأوروبية مجموعة راسل جامعات القرميد الأحمر المنحة المالية 143.5 مليون £ النوع جامعة عامة الكليات 6 الموقع الجغرافي إحداثيات 53°24′22″N 2°58′01″W  /  53.406°N 2.967°W  / 53.406; -2.967   المدينة ليفربول المكان   إنجلترا البلد   المملكة المتحدة رقم الهاتف 7942000 151 (44+) إحصاءات الطلاب 17,405 (سنة 2008) عضوية مجموعة رسل [1] أورسيد [2]   طلاب الدراسات العليا 3,860 الموقع www.liverpool.ac.uk تعديل   جامعة ليفربول مبنى فكتوريا جامعة ليفربول (بالإنجليزية: The University of Liverpool )) إحدى الجامعات البريطانية العريقة، تقع في مدينة ليفربول على الساحل الشمالي الغربي من أنجلترا . وهي عضو في مجموعة راسل للجامعات وتعتبر من ضمن جامعات الطوب الأحمر الستة. محتويات ...
          Read more