test.py

import numpy as np
import pandas as pd
import geopandas as gpd
import rasterio

# numpy
a = np.array([3, 8, -2, 43, 12, 1, 8])
b = np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])
c = np.arange(1, 25).reshape((2, 3, 4))
m = np.array([[ np.nan,  np.nan,  np.nan,  np.nan,  np.nan,   3.,   3.],
       [ np.nan,  np.nan,  np.nan,  np.nan,   4.,   6.,   4.],
       [ np.nan,  np.nan,  np.nan,  np.nan,   6.,   9.,   7.],
       [ np.nan,  61.,   9.,   4.,   9.,  10.,  16.],
       [ np.nan, 106., 132.,  11.,   6.,   6.,  27.],
       [ np.nan,  47., 254., 146.,   6.,   6.,  12.],
       [ np.nan,  31., 233., 340., 163.,  13.,  64.],
       [  3.,  39., 253., 383., 448., 152.,  39.],
       [  5.,  32., 199., 357., 414., 360.,  48.],
       [  7.,  49., 179., 307., 403., 370.,  55.]])

# pandas
d = {
    "name": pd.Series(["Beer-Sheva Center", "Beer-Sheva University", "Dimona"], name = "name"),
    "lines": pd.Series(np.array([4, 5, 1])),
    "city": pd.Series(["Beer-Sheva", "Beer-Sheva", "Dimona"]),
    "piano": pd.Series([False, True, False]),
    "lon": pd.Series([34.798443, 34.812831, 35.011635]),
    "lat": pd.Series([31.243288, 31.260284, 31.068616])
}
dat = pd.DataFrame(d)
dat

# geopandas
geom = gpd.points_from_xy(dat["lon"], dat["lat"])
geom = gpd.GeoSeries(geom)
layer = gpd.GeoDataFrame(dat, geometry = geom, crs = 4326)

# rasterio
dem = m.copy()
dem[np.isnan(dem)] = -9999
dem = dem.astype("int16")
transform = rasterio.transform.from_origin(662317, 3658412, 90, 90)