pandas dataframe
>>> 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 9pandas dataframe
>>> 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 9pandas dataframe
d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
col1 col2
0 1 3
1 2 4create 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)pandas
#for dropping a column in a dataframe
df = df.drop(['PassengerId'], axis = 1)
#for selecting all columns except one
df.iloc[:, df.columns != "Survived"]
#for checking nan values is a column
df['your column name'].isnull()pandas
df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index,
.....: columns=['A', 'B', 'C', 'D'])
.....:
In [137]: df = df.cumsum()
In [138]: plt.figure()
Out[138]: <Figure size 640x480 with 0 Axes>
In [139]: df.plot()
Out[139]: <matplotlib.axes._subplots.AxesSubplot at 0x7f53723daa10>
In [140]: plt.legend(loc='best')
Out[140]: <matplotlib.legend.Legend at 0x7f5369d93dd0>Copyright © 2021 Codeinu
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