I want to connect airplanes in origin (lat_1 lon_1) to dest(lat_2 lon_2). I use these data.

But unfortunately, I would get an incorrect result when creating LineString with shapely. I used everything like rotate and affine but it didn't correct.

Code:

cols = pd.read_csv("/content/dirct_lines.csv",sep=";")

line = cols[["callsign","latitude_1","longitude_1","latitude_2","longitude_2"]].dropna()

line['geometry'] = line.apply(lambda x: [(x['latitude_1'],
                                                         x['longitude_1']),
                                                         (x['latitude_2'],
                                                          x['longitude_2'])], axis = 1)
geoline = gpd.GeoDataFrame(line,geometry="geometry",
                      crs="EPSG:4326")

import matplotlib.pyplot as plt

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

ax = world.plot(figsize=(14,9),
    color='white', edgecolor='black')

geoline.plot(figsize=(14,9),ax=ax,facecolor = 'lightgrey', linewidth = 1.75,
           edgecolor = 'red',
           alpha = 2)
plt.show()

Shapely Output:

something that was interesting for me was that when I use Matplotlib to create lines everything is correct.

Code:

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(12, 8))


ax = fig.add_subplot(projection=ccrs.PlateCarree())


ax.stock_img()

org_lon, org_lat = cols["longitude_1"], cols["latitude_1"]
dst_lon, dst_lat = cols["longitude_2"], cols["latitude_2"]


plt.plot([org_lon, dst_lon], [org_lat, dst_lat],
        color='black', linewidth=0.5, marker='_',
        transform=ccrs.PlateCarree()
        )


plt.savefig(f"fight_path.png",dpi=60,facecolor = None, bbox_inches = 'tight', pad_inches = None)
plt.show()

Matplotlib Output:

What is the problem?

why isn't correct by shapely?

CodePudding user response：

it's just the way you are creating the geometry. Below works correctly.

import io
import geopandas as gpd
import pandas as pd
import shapely.geometry

df = pd.read_csv(
    io.StringIO(
        """callsign,latitude_1,longitude_1,latitude_2,longitude_2
HBAL102,-4.82114,-76.3194,-4.5249,-79.0103
AUA1028,-33.9635,151.181,48.1174,16.55
ABW120,41.9659,-87.8832,55.9835,37.4958
CSN461,33.9363,-118.414,50.0357,8.5723
ETH3730,25.3864,55.4221,50.6342,5.43903
"""
    )
)

geoline = gpd.GeoDataFrame(
    geometry=[
        shapely.geometry.LineString(points)
        for points in zip(
            gpd.points_from_xy(df["longitude_1"], df["latitude_1"]),
            gpd.points_from_xy(df["longitude_2"], df["latitude_2"]),
        )
    ],
    data=df,
)

import matplotlib.pyplot as plt

world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres"))
ax = world.plot(figsize=(14, 9), color="white", edgecolor="black")

geoline.plot(
    figsize=(14, 9),
    ax=ax,
    facecolor="lightgrey",
    linewidth=1.75,
    edgecolor="red",
)
plt.show()