用于转换 pandas 系列中的坐标并附加为其他系列的函数 [英] Function to convert coordinates in pandas series and append as additional series

问题描述

我希望将一系列坐标存储在熊猫数据框中，并定义一个函数，该函数将遍历每个条目，对其进行转换(将BNG Easting Northing转换为Lat和Long)并将其保存到以下位置的新列中同一行. Elise Huard的功能看起来它应该这样做

I'm looking to take as series of co-ordinates stored in a pandas dataframe and define a function that will go through each entry, transform it (BNG Easting Northing to Lat and Long) and save it to a new column in same row. This function by Elise Huard looks like it should do just this

def proj_transform(df):
    #bng = pyproj.Proj(init='epsg:27700')
    bng = pyproj.Proj("+init=EPSG:27700")
    #wgs84 = pyproj.Proj(init='epsg:4326')
    wgs84 = pyproj.Proj("+init=EPSG:4326")
    lats = pd.Series()
    lons = pd.Series()
    for idx, val in enumerate(df['Easting']):
        lon, lat = pyproj.transform(bng,wgs84,df['Easting'][idx], df['Northing'][idx])
        lats.set_value(idx, lat)
        lons.set_value(idx, lon)
    df['lat'] = lats
    df['lon'] = lons
    return df

但是一旦我尝试运行该功能，我就会收到以下错误消息.关于可能导致此问题的任何建议，或作为工作回合的替代方法的任何建议.

but im getting the following error once i try to run the function. Any advice on what might be causing it or an alternate approach as work round.

RuntimeError: non-convergent inverse meridional dist

使用的数据样本；

Site Reference  LA Reference    Start Date  Easting Northing
0   380500145   NaN 20130101    105175.0    105175.0
1   380500128   NaN 20060331    104000.0    104000.0
2   380500085   NaN 20030401    105055.0    105055.0
3   380500008   NaN 19980930    108480.0    108480.0
4   380500009   NaN 19980930    105415.0    105415.0
5   380500136   SHLAA20100101   105081.0    105081.0
6   380500038   NaN 19980930    105818.0    105818.0

推荐答案

如@ptrj所述；

RuntimeError: non-convergent inverse meridional dist

在这种情况下，是由数据中的NaN值引起的.

Was, in this instance, caused by NaN values in the data.

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