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Вивчайте Concatenation | Joining Data
Data Manipulation using pandas

bookConcatenation

Great! You've learned different ways of joining columns. Can we join two dataframes by rows? Surely, we can.

To join two dataframe, use the .concat() method of pandas, passing list of dataframes you want to join as the parameter. To perform this operation, both dataframes must have the same column names. Let's use splitted into two parts one of the dataframes used before and perform rows joining.

Note that .concat() is method of pandas, unlike the .merge() method. So you need to use pd.concat().

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# Importing library import pandas as pd # Loading data data1 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data_concat_1.csv') data2 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data_concat_2.csv') # Perform a left join df_res = pd.concat([data1, data2]) print(df_res)
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bookConcatenation

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Great! You've learned different ways of joining columns. Can we join two dataframes by rows? Surely, we can.

To join two dataframe, use the .concat() method of pandas, passing list of dataframes you want to join as the parameter. To perform this operation, both dataframes must have the same column names. Let's use splitted into two parts one of the dataframes used before and perform rows joining.

Note that .concat() is method of pandas, unlike the .merge() method. So you need to use pd.concat().

12345678910
# Importing library import pandas as pd # Loading data data1 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data_concat_1.csv') data2 = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/f2947b09-5f0d-4ad9-992f-ec0b87cd4b3f/section5/data_concat_2.csv') # Perform a left join df_res = pd.concat([data1, data2]) print(df_res)
copy

Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 5. Розділ 6
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