Example 1: dataframe create
>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
... columns=['a', 'b', 'c'])
>>> df2
a b c
0 1 2 3
1 4 5 6
2 7 8 9
Example 2: create dataframe with column names pandas
In [4]: import pandas as pd
In [5]: df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
In [6]: df
Out[6]:
Empty DataFrame
Columns: [A, B, C, D, E, F, G]
Index: []
Example 3: create a df in pandas
import pandas as pd
data = {'First Column Name': ['First value', 'Second value',...],
'Second Column Name': ['First value', 'Second value',...],
....
}
df = pd.DataFrame (data, columns = ['First Column Name','Second Column Name',...])
print (df)
Example 4: create dataframe panndas
import pandas as pd
data = {'First Column Name': ['First value', 'Second value',...],
'Second Column Name': ['First value', 'Second value',...],
....
}
df = pd.DataFrame (data, columns = ['First Column Name','Second Column Name',...])
print (df)
Example 5: dataframein python
import pandas as pd
data = {'First Column Name': ['First value', 'Second value',...],
'Second Column Name': ['First value', 'Second value',...],
....
}
df = pd.DataFrame (data, columns = ['First Column Name','Second Column Name',...])
Example 6: creating a pandas df
>>> d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
col1 col2
0 1 3
1 2 4