How to use 'pandas add column of zeros' in Python

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234def add_zeros(df, ctx):
235 """ Add values of zero where we believe appropriate."""
236 cellsize = ctx["sz"] * 1000.0
237 newrows = []
238 # loop over the grid looking for spots to add a zero
239 for y in np.arange(ctx["bnds2163"][1], ctx["bnds2163"][3], cellsize):
240 for x in np.arange(ctx["bnds2163"][0], ctx["bnds2163"][2], cellsize):
241 # search a 2x radius for any obs
242 poly = Polygon(
243 [
244 [x - cellsize, y - cellsize],
245 [x - cellsize, y + cellsize],
246 [x + cellsize, y + cellsize],
247 [x + cellsize, y - cellsize],
248 ]
249 )
250 df2 = df[df["geo"].within(poly)]
251 if df2.empty:
252 # Add a zero at this "point"
253 (lon, lat) = T2163_4326.transform(x, y)
254 if ctx["z"] != "no":
255 newrows.append(
256 {
257 "geo": Point(x, y),
258 "lon": lon,
259 "lat": lat,
260 "val": 0,
261 "nwsli": "Z%s" % (len(newrows) + 1,),
262 USEME: True,
263 "plotme": False,
264 "state": "Z",
265 }
266 )
267 continue
268 # For this grid cell, remove any values 20% of the max
269 maxval = df.at[df2.index[0], "val"]
270 df.loc[df2[df2["val"] >= (maxval * 0.2)].index, USEME] = True
271 df.loc[df2[df2["val"] >= (maxval * 0.2)].index, "plotme"] = True
272
273 return pd.concat(
274 [df, GeoDataFrame(newrows, geometry="geo")],
275 ignore_index=True,
276 sort=False,
277 )
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14def add_column_numpy_array(array, new_col):
15 placeholder = np.ones(array.shape[0])[:, np.newaxis]
16 result = np.hstack((array, placeholder))
17
18 if isinstance(new_col, np.ndarray):
19 assert array.shape[0] == new_col.shape[0], "input array row counts \
20 must be the same. \
21 Expected: {0}\
22 Actual: {1}".format(array.shape[0],
23 new_col.shape[0])
24 assert len(new_col.shape) <= 2, "new column must be 1D or 2D"
25
26 if len(new_col.shape) == 1:
27 new_col = new_col[:, np.newaxis]
28 return np.hstack((array, new_col))
29 elif isinstance(new_col, list):
30 assert len(new_col) == array.shape[0], "input array row counts \
31 must be the same. \
32 Expected: {0}\
33 Actual: {1}".format(len(array),
34 len(new_col))
35 new_col = np.array(new_col)
36 assert len(new_col.shape) == 1, "list elements cannot be iterable"
37 new_col = new_col[:, np.newaxis]
38 return np.hstack((array, new_col))
39 else:
40 placeholder = np.ones(array.shape[0])[:, np.newaxis]
41 result = np.hstack((array, placeholder))
42 result[:, -1] = new_col
43 return result

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