从熊猫数据透视表中选择一列

Question

I have the below pivot table which I created from a dataframe using the following code:

table = pd.pivot_table(df, values='count', index=['days'],columns['movements'], aggfunc=np.sum)

movements 0    1   2   3   4   5   6   7
days
0         2777 51  2                    
1         6279 200 7   3                
2         5609 110 32  4                
3         4109 118 101 8   3            
4         3034 129 109 6   2   2        
5         2288 131 131 9   2   1        
6         1918 139 109 13  1   1        
7         1442 109 153 13  10  1        
8         1085 76  111 13  7           1
9         845  81  86  8   8            
10        646  70  83  1   2   1   1

As you can see from pivot table that it has 8 columns from 0-7 and now I want to plot some specific columns instead of all. I could not manage to select columns. Lets say I want to plot column 0 and column 2 against index. what should I use for y to select column 0 and column 2?

plt.plot(x=table.index, y=??)

I tried with y = table.value['0', '2'] and y=table['0','2'] but nothing works.

Answer 1

You cannot select ndarray for y if you need those two column values in a single plot you can use:

plt.plot(table['0'])
plt.plot(table['2'])

If column names are intergers then:

plt.plot(table[0])
plt.plot(table[2])