how to convert points to lines in GeoPandas

a few lines of code to realize the point-to-line function¶

In the GIS data processing operation, the general point-to-line operation is often performed.
Here is a way to implement point-to-line conversion using Python.

1. Materials¶

• Pandas,
• GeoPandas,
• Shapely

Who knows the power of Pandas and GeoPandas
First look at the following point file, the format is a csv file with latitude and longitude coordinates. We first use pandas to present the data. The content is as follows:

import pandas as pd
import geopandas as gpd
from shapely.geometry import LineString,Point

fp = r'E:\Dev\data\BigRoads31.csv'
df = pd.read_csv(fp)
df.iloc[:30,:]

It can be seen that each row represents a point, and the last two columns of each row are coordinates. There are two other columns that we need to pay attention to. The FID column is the auto-increment ID of the data, and Num is a number. The subsequent dot-to-line will be based on these two columns.

Use Geopandas to print out the points, you can see the geographical distribution of the points, as shown in the figure below:

xy = [Point(xy) for xy in zip(df.Lng,df.Lat)]
pointDataFrame = gpd.GeoDataFrame(df,geometry=xy)
pointDataFrame.plot(figsize = (24, 24))

<matplotlib.axes._subplots.AxesSubplot at 0x1f5eeb3b390>

Anyone familiar with the vector data structure of GIS knows that a line is made up of points, and its physical structure is a series of points arranged in an orderly manner. According to this feature, we will carry out the point-to-line operation.

2. Point to line¶

There are rules to make a circle. No, there are rules to connect to a line. By looking at the above table, we convert points to lines according to the following rules:

1. Points with the same num value are merged into a line segment;
2. The arrangement order of the points on the line segment is FID according to the arrangement order in the table

The conversion process is as follows:

# grouping
dataGroup = df.groupby('Num')

# build data
tb = []
geomList = []
for name,group in dataGroup:
    # Separate the attribute information, and take the first 5 columns of the first row of each group as the data attributes
    tb.append(group.iloc[0,:5])
    # Pack the same group of points into a list
    xyList = [xy for xy in zip(group.Lng, group.Lat)]

    line = LineString(xyList)
    geomList.append(line)

# Point to line
geoDataFrame = gpd.GeoDataFrame(tb, geometry = geomList)

Let's print the result to see

geoDataFrame.iloc[:20,:]

As you can see, the data has been grouped by Num and merged into a LineString object.

3. Save the result as a geojson file¶

1. Save as geojson, two methods

# method 1
fp = r"E:\Dev\data\lineRoads.geojson"
geoDataFrame.to_file(fp, driver='GeoJSON', encoding="utf-8")

# method 2
json = geoDataFrame.to_json()
with open(fp,'w') as f:
    f.write(json)

1. Save as shp

shp = r"E:\Dev\data\lineRoads.shp"
geoDataFrame.to_file(shp,driver="ESRI Shapefile",encoding="utf-8")

4. Point to line complete code¶

Excluding some of the test verification code above, the point-to-line function can be realized in just a few lines. Good! ! !

import pandas as pd
import geopandas as gpd
from shapely.geometry import LineString,Point


def main():
    fp = r'E:\Dev\data\BigRoads31.csv'
    df = pd.read_csv(fp)

    #Group
    dataGroup = df.groupby('Num')

    #data Construction 
    tb = []
    geomList = []
    for name,group in dataGroup:
        # Separate the attribute information, and take the first 5 columns of the first row of each group as the data attributes
        tb.append(group.iloc[0,:5])
       # Pack the same group of points into a list
        xyList = [xy for xy in zip(group.Lng, group.Lat)]

        line = LineString(xyList)
        geomList.append(line)

    # Point to line
    geoDataFrame = gpd.GeoDataFrame(tb, geometry = geomList)

    fp = r"E:\Dev\data\lineRoads.geojson"
    geoDataFrame.to_file(fp, driver='GeoJSON', encoding="utf-8")

if __name__ == '__main__':
    main()