import numpy as np
import pandas as pd
import random

def xrange(x):
    return iter(range(x))

rnd_1 = [random.randrange(1, 20) for x in xrange(10)]

rnd_1

[16, 3, 18, 19, 1, 13, 17, 3 …

import numpy as np
import pandas as pd

ds = pd.Series([1, np.nan, 3, 4, 5])

ds

0    1.0
1    NaN
2    3.0
3    4.0
4    5.0
dtype: float64

# ds = ds.astype('int …

import numpy as np
import pandas as pd

df = pd.read_csv('abc.csv', sep=',', encoding='utf-8')

df

import numpy as np
import pandas as pd

df = pd.read_csv('abc2.csv')

df

import numpy as np
import pandas as pd

datatype = [('Science', 'int32'), ('Maths', 'int32')]

current_values = np.zeros(3, dtype=datatype)

current_index = ['Row '+str(i) for i in range(1, 4)]

df = pd.DataFrame(current_values, index=current_index)

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('abc.csv')

df.shape

(7, 5)

df

import numpy as np
import pandas as pd

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

df

import numpy as np
import pandas as pd

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

df

import numpy as np
import pandas as pd

df = pd.read_csv('data1.csv')

df