[Python] How to break down a column which contains several different features, so that a new...

I want to break down a column which contains several different features, so that a new column is built for each feature, also taking as column name the feature name. I already tried with:

data = {'col1': ["a=1", "b=2", "c=3"]}
col1
0 a=1
1 b=2
2 c=3

df['col2'] = df['col1'].apply(lambda x: pd.Series(x[0]))
df['col3'] = df['col1'].apply(lambda x: pd.Series(x[1]))
df['col4'] = df['col1'].apply(lambda x: pd.Series(x[2]))

#df['col5'] = df['col1'].apply(lambda x:x[3] if len(x) > 3 else None)
print(df)
new_df= df.drop('col1', axis=1)
print(new_df)


But the strings are split, this was the output:

col2 col3 col4
0 a = 1
1 b = 2
2 c = 3


This is my input:

Column1
“Height = 12”
…. (14 rows)
“Height = 18”
…. (16 rows)
“Weight = 40”
…. (17 rows)
“Weight = 50”
…. (3 rows)
“Colour = red”
…. (8 rows)
“Colour = yellow”


This is what I need:

Height Weight Colour
12 NaN NaN
… (14 rows) … (14 rows) … (14 rows)
18 NaN NaN
… (16 rows) … (16 rows) … (16 rows)
NaN 40 NaN
… (17 rows) … (17 rows) … (17 rows)
NaN 50 NaN
… (3 rows) … (3 rows) … (3 rows)
NaN NaN red
… (8 rows) … (8 rows) … (8 rows)
NaN NaN yellow
… (2 rows) … (2 rows) … (2 rows)


How to manage it? Thanks in advance.

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