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I have scrapped some contents from a web site and saved the data into some different csv files.

For example,

csv1:-

row number    time              price

1              2018/01/01        12

2              2018/01/02        15

csv2:-

row number    time              address

1              2018/01/01        MI

2              2018/01/02        AR

Now, how can I Merge the two csv files into one csv file and below is the format of new csv.

row number    time              price         address

1              2018/01/01        12             MI

2              2018/01/02        15             AR

Can someone help me?

This question has confused me several days.

Thanks a lot!

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You may use Pandas df.append(). You may reference this answer.

If these CSVs have different columns, then individually read each one of them as a Pandas DataFrame, and then create a new DataFrame referencing columns from previously created individual DataFrames.

For your case, you can also use pd.merge command of pandas:

In [488]: df1 = pd.read_csv('/home/mayankp/Documents/Personal/stackoverflow/csv1.csv')



In [498]: df1

Out[498]: 

   row_number        time  price

0           1  2018/01/01     12

1           2  2018/01/02     15



In [490]: df2 = pd.read_csv('/home/mayankp/Documents/Personal/stackoverflow/csv2.csv')



In [499]: df2

Out[499]: 

   row_number        time address

0           1  2018/01/01      MI

1           2  2018/01/02      AR



In [500]: pd.merge(df1,df2, on=['row_number','time'])

Out[500]: 

   row_number        time  price address

0           1  2018/01/01     12      MI

1           2  2018/01/02     15      AR

Try the following:

import pandas as pd



csv1 = pd.read_csv("file1.csv")

csv2 = pd.read_csv("file2.csv")



csv_out = csv1.merge(csv2, on=['row number','time'])

csv_out.to_csv("file_out.csv", index=False)

Hope it helps.

I know you have csv files but here I am just showing and trying to help you by manually creating DataFrames as you have mentioned in the problem.

• DataFrame:- https://www.tutorialspoint.com/python_pandas/python_pandas_dataframe.htm




• https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html - Here you can visit and find more about the parameters to merge() method defined on DataFrame.

Below is the code that you're looking for.

>>> import pandas as pd

>>>

>>> dri = pd.date_range("2018/01/01", periods=2, freq="d")

>>>

>>> df = pd.DataFrame({"time": dri, "price": [12, 15]}, index = [1, 2])

>>> df

        time  price

1 2018-01-01     12

2 2018-01-02     15

>>>

>>> df2 = pd.DataFrame({"time": dri, "address": ["MI", "AR"]}, index=[1, 2])

>>> df2

        time address

1 2018-01-01      MI

2 2018-01-02      AR

>>>

>>> # https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html

...

>>>

>>> df.merge(df2, on = "time", how = "inner", left_index = True)

        time  price address

1 2018-01-01     12      MI

2 2018-01-02     15      AR

>>>

By default, pandas does not include labels for index on left of DataFrame. If you really wish to have labels for the index of DataFrame as you have mentioned (In your case, that is row number), have a look into below executed statements on Python interactive terminal.

>>> df.index.name = "row number"

>>> df

                 time  price

row number

1          2018-01-01     12

2          2018-01-02     15

>>>

>>> df2.index.name = "row number"

>>>

>>> df2

                 time address

row number

1          2018-01-01      MI

2          2018-01-02      AR

>>>

>>> df.merge(df2, on = "time", how = "inner", left_index = True)

                 time  price address

row number

1          2018-01-01     12      MI

2          2018-01-02     15      AR

>>>