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Appending Two DataFrames in Pandas
Let's say we have two dataframes with the same attributes and they share a physical attribute that may vary. We can combine both dataframes and differentiate using this physical attribute to make handling csv files easier.
For example, if we have descriptions of colors of skin, hair, and eyes for two dataframes, one for males and one for females, we can add a column at the end that signifies whether the attributes in a certain row belong to a male or female, all in the same dataframe (population_df) instead of 2.
Import pandas as pd
males_df = pd.read_csv('males.csv')
females_df = pd.read_csv('females.csv')gender_male = np.repeat('male', males_df.shape[0])
gender_female = np.repeat('female', females_df.shape[0])population_df = males_df.append(females_df)population_df.to_csv('Filename.csv'), index=False)Note: You can make sure that you've successfully appended your two dataframes by using .shape
population_df.shapeIf the number is the sum of the two dataframe counts, proceed with your work
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