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 9
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 9
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>
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