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

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def add_zeros(df, ctx):
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    """ Add values of zero where we believe appropriate."""
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    cellsize = ctx["sz"] * 1000.0
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    newrows = []
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    # loop over the grid looking for spots to add a zero
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    for y in np.arange(ctx["bnds2163"][1], ctx["bnds2163"][3], cellsize):
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        for x in np.arange(ctx["bnds2163"][0], ctx["bnds2163"][2], cellsize):
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            # search a 2x radius for any obs
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            poly = Polygon(
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                [
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                    [x - cellsize, y - cellsize],
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                    [x - cellsize, y + cellsize],
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                    [x + cellsize, y + cellsize],
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                    [x + cellsize, y - cellsize],
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                ]
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            )
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            df2 = df[df["geo"].within(poly)]
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            if df2.empty:
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                # Add a zero at this "point"
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                (lon, lat) = T2163_4326.transform(x, y)
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                if ctx["z"] != "no":
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                    newrows.append(
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                        {
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                            "geo": Point(x, y),
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                            "lon": lon,
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                            "lat": lat,
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                            "val": 0,
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                            "nwsli": "Z%s" % (len(newrows) + 1,),
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                            USEME: True,
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                            "plotme": False,
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                            "state": "Z",
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                        }
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                    )
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                continue
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            # For this grid cell, remove any values 20% of the max
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            maxval = df.at[df2.index[0], "val"]
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            df.loc[df2[df2["val"] >= (maxval * 0.2)].index, USEME] = True
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            df.loc[df2[df2["val"] >= (maxval * 0.2)].index, "plotme"] = True
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    return pd.concat(
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        [df, GeoDataFrame(newrows, geometry="geo")],
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        ignore_index=True,
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        sort=False,
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    )

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def add_column_numpy_array(array, new_col):
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    placeholder = np.ones(array.shape[0])[:, np.newaxis]
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    result = np.hstack((array, placeholder))
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    if isinstance(new_col, np.ndarray):
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        assert array.shape[0] == new_col.shape[0], "input array row counts \
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                                                    must be the same. \
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                                                    Expected: {0}\
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                                                    Actual: {1}".format(array.shape[0],
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                                                                        new_col.shape[0])
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        assert len(new_col.shape) <= 2, "new column must be 1D or 2D"
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        if len(new_col.shape) == 1:
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            new_col = new_col[:, np.newaxis]
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        return np.hstack((array, new_col))
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    elif isinstance(new_col, list):
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        assert len(new_col) == array.shape[0], "input array row counts \
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                                                    must be the same. \
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                                                    Expected: {0}\
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                                                    Actual: {1}".format(len(array),
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                                                                        len(new_col))
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        new_col = np.array(new_col)
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        assert len(new_col.shape) == 1, "list elements cannot be iterable"
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        new_col = new_col[:, np.newaxis]
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        return np.hstack((array, new_col))
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    else:
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        placeholder = np.ones(array.shape[0])[:, np.newaxis]
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        result = np.hstack((array, placeholder))
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        result[:, -1] = new_col
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        return result