Nested list to pandas DataFrame with fixed number of columns

Question

New to Python. Would like to convert below list to pandas dataframe with fixed number of columns

[['Teja'], ['22', 'Male'], ['Viha'], ['Female'], ['Male'], ['Vinay'], ['32', 'Female'], ['Sowmya']]

IS your list organized as [[name],[age,gender]] or as your example? — alphaBetaGamma
– alphaBetaGamma, Commented Dec 6, 2020 at 18:21
No. it is not organized as [[name],[age,gender]]. It is just a random list — Swathi
– Swathi, Commented Dec 6, 2020 at 18:22
What have you tried so far? Please include your code attempts — William Baker Morrison
– William Baker Morrison, Commented Dec 6, 2020 at 19:08

Hanumanth Reddy Aredla · Accepted Answer · 2020-12-06 18:44:04Z

1

Hope this is what you are looking at.

import pandas as pd

a = [
    ["Teja"],
    ["22", "Male"],
    ["Viha"],
    ["Female"],
    ["Male"],
    ["Vinay"],
    ["32", "Female"],
    ["Sowmya"],
]

name = []
age = []
gender = []
for item in a:
    if "Male" in item or "Female" in item:
        if item[0].isnumeric():
            age.append(item[0])
            gender.append(item[1])
        else:
            age.append("None")
            gender.append(item[0])
        continue
    name.append(item[0])

data = {"name": name, "age": age, "gender": gender}

print(name, age, gender)

df = pd.DataFrame(data)

print(df)

answered Dec 6, 2020 at 18:44

Hanumanth Reddy Aredla

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Comments

Harshith Reddy · Accepted Answer · 2020-12-06 18:36:13Z

0

Create a dictionary like this:

d = {
    'name'  : ['Teja', 'Viha', 'Vinay', 'Sowmya'],
    'age'   : [22, None, None, 32],
    'gender': ['Male', 'Female', 'Male', 'Female']
}
my_dataframe = pandas.DataFrame(d)
print(my_dataframe)

The output would be like:

     name   age  gender
0    Teja  22.0    Male
1    Viha   NaN  Female
2   Vinay   NaN    Male
3  Sowmya  32.0  Female

answered Dec 6, 2020 at 18:36

Harshith Reddy

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1 Comment

Michael Over a year ago

The question was how to convert existing data, not how to type it and make dataframe

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