Creating polygon grid using Geopandas

Previous answer gives correct result, but I allowed myself to improve the code, to avoid many unnecessary lines, as well as iterating on indexes instead of values on the list.

import geopandas as gpd
from shapely.geometry import Polygon
import numpy as np
points = gpd.read_file('points.shp')

xmin,ymin,xmax,ymax = points.total_bounds

length = 1000
wide = 1200

cols = list(range(int(np.floor(xmin)), int(np.ceil(xmax)), wide))
rows = list(range(int(np.floor(ymin)), int(np.ceil(ymax)), length))
rows.reverse()

polygons = []
for x in cols:
    for y in rows:
        polygons.append( Polygon([(x,y), (x+wide, y), (x+wide, y-length), (x, y-length)]) )

grid = gpd.GeoDataFrame({'geometry':polygons})
grid.to_file("grid.shp")

The main idea might be the same, but we are creating now much less useless variables and whole code is clearer to understand

There are many solutions.

One of them

 import geopandas as gpd
 from shapely.geometry import Polygon
 import numpy as np
 points = gpd.read_file('points.shp')
 xmin,ymin,xmax,ymax =  points.total_bounds
 width = 2000
 height = 1000
 rows = int(np.ceil((ymax-ymin) /  height))
 cols = int(np.ceil((xmax-xmin) / width))
 XleftOrigin = xmin
 XrightOrigin = xmin + width
 YtopOrigin = ymax
 YbottomOrigin = ymax- height
 polygons = []
 for i in range(cols):
    Ytop = YtopOrigin
    Ybottom =YbottomOrigin
    for j in range(rows):
        polygons.append(Polygon([(XleftOrigin, Ytop), (XrightOrigin, Ytop), (XrightOrigin, Ybottom), (XleftOrigin, Ybottom)])) 
        Ytop = Ytop - height
        Ybottom = Ybottom - height
    XleftOrigin = XleftOrigin + width
    XrightOrigin = XrightOrigin + width

grid = gpd.GeoDataFrame({'geometry':polygons})
grid.to_file("grid.shp")

You can also truncate the grid (convex hull):

But one of the most interesting is to use the module gpd_lite_toolboox)