Python graphing dates*quantity - python-3.x

Question

I have a dataset with 1915 rows, that has an entry date col and a qty col contained in it. i.e.
10/22/2018 qty:1
10/22/2018 qty:3
11/22/2017 qty:1
Is it possible to edit the code below to multiply the count of dates by the qty associated with it? I've been fiddling around with where to put the multiplier but am stumped. This is the code I have running so far (without multiplier).
import pandas as pd
import matplotlib.pyplot as plt; plt.rcdefaults()
import matplotlib.dates as mdates
import numpy as np
import matplotlib.pyplot as plt
quotes = pd.read_csv("PO25474.csv")
quotes["ENTRY_DATE"] = quotes["ENTRY_DATE"].astype("datetime64")
plt.figure(figsize=(20, 10))
ax = (quotes["ENTRY_DATE"].groupby([quotes["ENTRY_DATE"].dt.year,\
quotes["ENTRY_DATE"].dt.month]).count().plot(kind="bar"))
ax.set_xlabel("quotes by month")
ax.set_ylabel("count")
ax.set_title("title")
plt.show()

Answer 1

I solved it. Had to put in QTY after the groupby and swap out count with sum.
import pandas as pd
import matplotlib.pyplot as plt; plt.rcdefaults()
import matplotlib.dates as mdates
import numpy as np
quotes = pd.read_csv("PO25474.csv")
qty = quotes[["ENTRY_DATE" , "QTY"]]
quotes["ENTRY_DATE"] = quotes["ENTRY_DATE"].astype("datetime64")
plt.figure(figsize=(12, 5))
ax = (quotes.groupby([quotes["ENTRY_DATE"].dt.year, quotes["ENTRY_DATE"].dt.month])
['QTY'].sum().plot(kind="bar"))
ax.set_xlabel("quotes by month")
ax.set_ylabel("count")
ax.set_title("PO25474")
plt.show()