Plot multiple rows of dataframe in pandas for specific columns

Question

df

SKU  Comp Brand  Jan_Sales  Feb_Sales  Mar_sales Apr_sales  Dec_sales..
 A    AC   BA      122        100        50        200         300
 B    BC   BB      100        50         80        90          250
 C    CC   BC       40        30        100        10          11

and so on

Now I want a graph which will plot Jan sales, feb sales and so on till dec in one line for SKU A, Similarly one line on the same graph for SKU B and same way for SKU C.

I read few answers which say that I need to transpose my data. Something like below

 df.T. plot()

However my first column is SKU, and I want to plot based on that. Rest of the columns are numeric. So I want that on each line SKU Name should be mentioned. And plotting should be row wise

EDIT(added after receiving some answers as I am facing this issue in few other datasets):

lets say I dont want columns Company, brand etc, then what to do

jezrael · Accepted Answer · 2020-01-30 08:41:13Z

2

Use DataFrame.set_index for convert SKU to index and then tranpose:

df.set_index('SKU').T.plot()

answered Jan 30, 2020 at 8:41

jezrael

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Chris · Accepted Answer · 2020-01-30 08:41:10Z

1

Use set_index then transpose:

df.set_index("SKU").T.plot()

Output:

answered Jan 30, 2020 at 8:41

Chris

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2 Comments

noob Over a year ago

if I want to include only few columns say in my graph then what to do? Lets say there are columns like company and brand etc of SKU which I dont want to include in my graph, then what to do ? How to include only specific columns

Chris Over a year ago

If you were to, say, use only A and B, try using loc: df.set_index("SKU").loc[["A","B"]].T.plot(). Or, if you want to filter out C, use drop: df.set_index("SKU").drop(["C"]).T.plot().

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