pulling data out of bins in density map created with matplotlib - matplotlib

Question

I have created a lightning density map using lines of data representing lightning strikes. One line is shown below:
1996-01-17 03:54:35.853 44.9628 -78.9399 -37.9
Now that I have applied these lines of data to the density map and distributed them into their appropriate bins based on Lat/Long, I would like to pull the data back out specific to the bin that it fell into so that I can manipulate that data further.
I have tried to find answers to this online but have failed to find anything that is specific to what I am trying to do. Any and all help is greatly appreciated!
my code:
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.axes as ax
import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from metpy.plots import USCOUNTIES
from matplotlib.axes import Axes
from cartopy.mpl.geoaxes import GeoAxes
GeoAxes._pcolormesh_patched = Axes.pcolormesh
import datetime
fig, ax = plt.subplots(figsize=(15,15),subplot_kw=dict(projection=ccrs.Stereographic(central_longitude=-76, central_latitude=43)))
ax.set_extent([-79, -73, 42, 45],ccrs.Geodetic())
ax.add_feature(USCOUNTIES.with_scale('500k'), edgecolor='gray', linewidth=0.25)
ax.add_feature(cfeature.STATES.with_scale('50m'))
winter = [12, 1, 2]
summer = [6, 7, 8]
seasondata = []
lons=[]
lats=[]
f = open("2007-2016.txt", "r")
for line in f.readlines():
parts = line.split()
dates = parts[0]
charges = float(parts[4])
date = datetime.datetime.strptime(dates, "%Y-%m-%d")
#if date.month in summer:
if date.month in winter:
seasondata.append(line)
if charges <= 0:
seasondata.append(line)
lon = float(parts[3])
lat = float(parts[2])
lons.append(lon)
lats.append(lat)
if charges >= 15:
seasondata.append(line)
lon = float(parts[3])
lat = float(parts[2])
lons.append(lon)
lats.append(lat)
lons=np.array(lons)
lats=np.array(lats)
ax.set_title('2007-2016 Jan, Feb, Dec: Lightning Density', loc ='Left')
xynps = (ax.projection.transform_points(ccrs.Geodetic(), lons, lats))
bins=[300,240]
h2d, xedges, yedges, im = ax.hist2d(xynps[:,0], xynps[:,1], bins=bins, cmap=plt.cm.YlOrRd, zorder=10, alpha=0.4)
lons=[]
lats=[]
f = open("turbine.txt", "r")
for line in f.readlines():
parts = line.split()
lat=float(parts[0])
lon=float(parts[1])
lats.append(lat)
lons.append(lon)
markerSymbol='o'
markerSize=10
ax.scatter(lons, lats, transform=ccrs.PlateCarree(), marker = markerSymbol, s=markerSize, c='b')
cbar = plt.colorbar(im, fraction=0.046, pad=0.04)
cbar.set_label("Flashes per 2km^2")
plt.show()