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Edit and run



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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt



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starting_date = '20160701'
sample_numpy_data = np.array(np.arange(24)).reshape((6,4))
dates_index = pd.date_range(starting_date, periods=6)
sample_df = pd.DataFrame(sample_numpy_data, index=dates_index, columns=list('ABCD'))
sample_df



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sample_df_2 = sample_df.copy()
sample_df_2['Fruits'] = ['apple', 'orange','banana','strawberry','blueberry','pineapple']
sample_df_2

Setting a new column automatically aligns the data by the indexes



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Setting values by label



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Setting values by position

documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.iat.html

iat provides integer based lookups



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Setting by assigning with a numpy array



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	A	B	C	D
2016-07-01	0	1	2	3
2016-07-02	4	5	6	7
2016-07-03	8	9	10	11
2016-07-04	12	13	14	15
2016-07-05	16	17	18	19
2016-07-06	20	21	22	23

	A	B	C	D	Fruits
2016-07-01	0	1	2	3	apple
2016-07-02	4	5	6	7	orange
2016-07-03	8	9	10	11	banana
2016-07-04	12	13	14	15	strawberry
2016-07-05	16	17	18	19	blueberry
2016-07-06	20	21	22	23	pineapple