import pandas as pd
import numpy as np
# pandas as an array
data = np.array(['p','a','n','d','a', 's'])
myseries = pd.Series(data)
print(myseries)​
import pandas as pd
d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)
print(df)
Output :
col1 col2
0 1 3
1 2 4
import pandas as pd
country_population = {'India': 1600000000, 'China': 1730000000, 'USA': 390000000, 'UK': 450000000}
population = pd.Series(country_population)
#print(population)
country_land = {'India': '2547869 hectares', 'China': '9543578 hectares', 'USA': '5874658 hectares', 'UK': '6354652 hectares'}
area = pd.Series(country_land)
#print(area)
df = pd.DataFrame({'Population': population, 'SpaceOccupied': area})
print(df)
import pandas as pd
index_A = pd.Index([1, 3, 5, 7, 9])
index_B = pd.Index([2, 3, 5, 7, 11])
import pandas as pd
import numpy as np
N=20
df = pd.DataFrame({
'A': pd.date_range(start='2021-01-18',periods=N,freq='D'),
'x': np.linspace(0,stop=N-1,num=N),
'y': np.random.rand(N),
'C': np.random.choice(['Low','Medium','High'],N).tolist(),
'D': np.random.normal(100, 10, size=(N)).tolist()
})
#reindex the DataFrame
df_reindexed = df.reindex(index=[0,2,5], columns=['A', 'C', 'B'])
print (df_reindexed)​
Output :
A C B
0 2021-01-18 Medium NaN
2 2021-01-20 High NaN
5 2021-01-23 Low NaN
import pandas as pd
import numpy as np
df1 = pd.DataFrame(np.random.randn(4, 3), columns=['col1', 'col2', 'col3'])
df2 = pd.DataFrame(np.random.randn(2, 3), columns=['col1', 'col2', 'col3'])
print(df2.reindex_like(df1))
Output :
col1 col2 col3
0 -0.641715 1.031070 -0.208415
1 -1.560385 -0.584403 0.291666
2 NaN NaN NaN
3 NaN NaN NaN
Reindexing with using methods(bfill or ffill)
import pandas as pd
import numpy as np
df1 = pd.DataFrame(np.random.randn(4, 3), columns=['col1', 'col2', 'col3'])
df2 = pd.DataFrame(np.random.randn(2, 3), columns=['col1', 'col2', 'col3'])
print(df2.reindex_like(df1, method='ffill'))
Output :
col1 col2 col3
0 1.332612 -0.479218 -1.016999
1 -1.091319 -0.844934 -0.492755
2 -1.091319 -0.844934 -0.492755
3 -1.091319 -0.844934 -0.492755
import pandas as pd
import numpy as np
df1 = pd.DataFrame(np.random.randn(4, 3), columns=['col1', 'col2', 'col3'])
df2 = pd.DataFrame(np.random.randn(2, 3), columns=['col1', 'col2', 'col3'])
print(df2.reindex_like(df1, method='bfill'))
Output :
col1 col2 col3
0 0.526663 -0.450748 0.791112
1 -1.805287 0.641050 1.864871
2 NaN NaN NaN
3 NaN NaN NaN