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Shivani Upare
2 years ago
#import the pandas library
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(5,3), index=['a', 'c', 'e', 'f','h'],columns=['Column1',
'Column2', 'Column3'])
data = data.reindex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
print(data)
Column1 Column2 Column3
a -0.067397 -1.570255 -0.898418
b NaN NaN NaN
c 1.311982 1.972563 0.743876
d NaN NaN NaN
e 0.516474 -0.436298 -0.336320
f 0.587955 0.928367 1.014634
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(5, 3), index=['a', 'c', 'e', 'f',
'h'],columns=['Column1','Column2', 'Column3'])
data = data.reindex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
print(data['Column1'].isnone())
a false
b true
c false
d true
e false
f false
g true
h false
Name: Column1, dtype: bool
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(3, 3), index=['a', 'c', 'e'],columns=['Column1',
'Column2', 'Column3'])
data = data.reindex(['a', 'b', 'c'])
print(data)
print
("NaN replaced with '0':")
print
(df.fillna(0))
Column1 Column2 Column3
a -1.145282 -1.204689 -0.011520
b NaN NaN NaN
c 1.054585 0.450895 -1.765849
NaN replaced with '0':
Column1 Column2 Column3
a 1.028044 -0.059059 0.814159
b 0.000000 0.000000 0.000000
c -0.093614 0.502746 -0.979775
d 0.000000 0.000000 0.000000
e -0.926268 0.819182 0.057756
f 0.654027 1.196219 1.441782
g 0.000000 0.000000 0.000000
h 0.888539 0.472792 -1.369401
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(5,3), index=['a', 'c', 'e', 'f',
'h'],columns=['Column1','Column2', 'Column3'])
data = data.reindex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
print(data.fillna(method='pad'))
Column1 Column2 Column3
a 0.863373 0.113220 0.167150
b 0.863373 0.113220 0.167150
c 0.175815 0.526849 0.074818
d 0.175815 0.526849 0.074818
e -0.203824 -0.921412 1.200571
f 0.864100 1.263429 -0.200021
g 0.864100 1.263429 -0.200021
h 1.774977 -0.118278 0.415756
import pandas as pd
import numpy as np
data =pd.DataFrame(np.random.randn(5, 3), index=['a', 'c', 'e', 'f',
'h'],columns=['Column1','Column2', 'Column3'])
data = data.reindex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
print(data.dropna())
Column1 Column2 Column3
a -0.316294 0.890039 0.349166
c -1.297559 0.113461 0.884424
e -2.175159 0.379806 2.231736
f -2.385318 1.803276 -0.342873
h 1.372849 1.482879 -0.349323
import pandas as pd
import numpy as np
data = pd.DataFrame({'Column1':[10,20,30,40,50,2000],
'Column2':[1000,0,30,40,50,60]})
print(data.replace({1000:10,2000:60}))
Column1 Column2
0 10 10
1 20 0
2 30 30
3 40 40
4 50 50
5 60 60