python - pd.read_json() 到 pandas 中的数据框

Question

我以前从未使用过 json 文件。目前这就是我正在做的:

df = pd.read_json("precincts-with-results.geojson.gz")
df['features']

这是上面的结果:

{'type': 'Feature',
 'properties': {'GEOID': '05047-1-A (Oz Wd 1)',
  'votes_dem': 79,
  'votes_rep': 279,
  'votes_total': 366,
  'votes_per_sqkm': 54.2,
  'pct_dem_lead': -54.6},
 'geometry': {'type': 'MultiPolygon',
  'coordinates': [[[[-93.88536364311612, 35.483758439321655],
     [-93.8840470388143, 35.483727092097084],
     [-93.88403177163875, 35.483726728784056],
     [-93.88403177478405, 35.48372661335151],
     [-93.87956152062023, 35.483586322546344],
     [-93.87520339804045, 35.48339873745174],
     [-93.87534656033012, 35.480428139370346],
     [-93.87604589142236, 35.48045051399295], ...

我想要一个看起来像这样的数据框:

GEOID                   votes_dem     votes_rep     votes_total      votes_per_sqkm       pct_dem_lead
05047-1-A (Oz Wd 1)       79               279         366             54.2                 -54.6 
  

您可以在此处下载数据集(大小 264 mb):https://int.nyt.com/newsgraphics/elections/map-data/2020/national/precincts-with-results.geojson.gz

感谢帮助和代码!!

Answer 1

这对我有用

import pandas as pd

filename = 'precincts-with-results.geojson.gz'
df = pd.read_json(filename)
features = df['features']
properties = [_['properties'] for _ in features.values]
collect_properties = {_: list() for _ in properties[0].keys()}
for record in properties:
    for col_name, value in record.items():
        collect_properties[col_name].append(value)

new_df = pd.DataFrame.from_dict(collect_properties).set_index('GEOID')
print(new_df)

结果看起来像

                        votes_dem  votes_rep  ...  votes_per_sqkm  pct_dem_lead
GEOID                                          ...                              
05047-1-A (Oz Wd 1)           79.0      279.0  ...            54.2         -54.6
05149-11 - Dutch Creek         6.0       31.0  ...             0.3         -67.6
05081-Franklin Township       53.0      383.0  ...             3.8         -73.3
05027-McNeil City             64.0       68.0  ...            41.9          -2.9
05027-Taylor Township         67.0      342.0  ...             1.7         -65.0
                            ...        ...  ...             ...           ...
56007-01-01                  173.0      300.0  ...            21.8         -26.1
56045-05-01                   70.0      390.0  ...           259.5         -66.7
56045-05-02                   67.0      376.0  ...            66.5         -68.1
56045-05-03                   63.0      419.0  ...           141.4         -71.5
56041-130                    168.0      654.0  ...             1.7         -57.1
[146596 rows x 5 columns]