Expand Cells Containing Lists Into Their Own Variables In Pandas
/* import pandas */
import pandas as pd
/* create a dataset */
raw_data = {'score': [1,2,3],
'tags': [['apple','pear','guava'],['truck','car','plane'],['cat','dog','mouse']]}
df = pd.DataFrame(raw_data, columns = ['score', 'tags'])
/* view the dataset */
df
score | tags | |
---|---|---|
0 | 1 | apple,pear,guava |
1 | 2 | truck,car,plane |
2 | 3 | cat,dog,mouse |
/* expand df.tags into its own dataframe */
tags = df['tags'].apply(pd.Series)
/* rename each variable is tags */
tags = tags.rename(columns = lambda x : 'tag_' + str(x))
/* view the tags dataframe */
tags
tag_0 | tag_1 | tag_2 | |
---|---|---|---|
0 | apple | pear | guava |
1 | truck | car | plane |
2 | cat | dog | mouse |
/* join the tags dataframe back to the original dataframe */
pd.concat([df[:], tags[:]], axis=1)
score | tags | tag_0 | tag_1 | tag_2 | |
---|---|---|---|---|---|
0 | 1 | apple,pear,guava | apple | pear | guava |
1 | 2 | truck,car,plane | truck | car | plane |
2 | 3 | cat,dog,mouse | cat | dog | mouse |
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
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- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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