import pandas as pd

data = {
    'city' : ['Toronto', 'Montreal', 'Waterloo'],
    'points' : [80, 70, 90]
}

data

{'city': ['Toronto', 'Montreal', 'Waterloo'], 'points': [80, 70, 90]}

type(data)

dict

df = pd.DataFrame(data)

df

df = df.assign(code = [1, 2, 3])

df

import numpy as np
import pandas as pd

# Check the student passed either math or passed at least in 2 subjects. If no condidition matched, consider them as failed
def pass_math_or_two_subjects(row):
    if(row.maths > 34):
        return …

import pandas as pd

data = {
    'city' : ['Toronto', 'Montreal', 'Waterloo'],
    'points' : [80, 70, 90]
}

data

{'city': ['Toronto', 'Montreal', 'Waterloo'], 'points': [80, 70, 90]}

type(data)

dict

df = pd.DataFrame(data)

df

import pandas as pd

data = {
    'city' : ['Toronto', 'Montreal', 'Waterloo', 'Toronto', 'Waterloo', 'Toronto', 'Toronto'],
    'points' : [80, 70, 90, 85, 79, 82, 200]
}

data

{'city': ['Toronto',
  'Montreal',
  'Waterloo',
  'Toronto',
  'Waterloo',
  'Toronto',
  'Toronto'],
 'points': [80, 70, 90, 85, 79 …

import numpy as np
import pandas as pd

marks = [
    [90, 87],
    [90, 95],
    [92, 95]
]

marks

[[90, 87], [90, 95], [92, 95]]

df = pd.DataFrame(marks, columns=['maths', 'science'])

df

import numpy as np
import pandas as pd

data = {
    'sam' : ['archery', 'badminton', 'athletics', 'cycling_road', 'canoe_sprint', 'boxing'],
    'medal' : ['gold', 'silver', 'bronze', 'gold', 'gold', 'silver']
}

df = pd.DataFrame(data)

df

import numpy as np
import pandas as pd

df = pd.read_csv('marks.csv')

df

import numpy as np
import pandas as pd

df = pd.read_csv("/Users/rajacsp/datasets/sales_data_types.csv")

df

import numpy as np
import pandas as pd

csv = pd.DataFrame.from_csv('uk-500.csv')

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: from_csv is deprecated. Please use read_csv(...) instead. Note that …

import numpy as np
import pandas as pd

def apply_math_special(row):
    return (row.maths *2 + (row.language/2) + (row.history/3) + (row.science/4))

df = pd.read_csv('abc.csv')

df