Building GeoDataFrame row by row

I am trying to build GeoDataFrame row by row, from an empty one. The equivalent using only pandas would be something like this :

df = pandas.DataFrame(columns=['a','b','c','d'])    
df.loc['y'] = pandas.Series({'a':1, 'b':5, 'c':2, 'd':3})

(from [this answer])

---

My current method

So far, I build a Python list of dict with a specific structure, and then use it to create a GeoFataFrame, here is a complete example :

import geopandas as gpd
from shapely.geometry import  Point

my_dict = {
  '007': {
    'name': 'A',
    'lat': 48.843664, 
    'lon': 2.302672,
    'type': 'small'
  },
  '008': {
    'name': 'B',
    'lat': 50.575813,
    'lon': 7.258148,
    'type': 'medium'
  },
  '010': {
    'name': 'C',
    'lat': 47.058420, 
    'lon': 15.437464,
    'type': 'big'
  }
}

tmp_list = []
for item_key, item_value in my_dict.items() :
  tmp_list.append({
    'geometry' : Point(item_value['lon'], item_value['lat']),
    'id': item_key,
    'name': item_value ['name'],
    'type': item_value ['type']
   })
my_gdf = gpd.GeoDataFrame(tmp_list)
print(my_gdf.head())

Here is the result :

                    geometry   id name    type
0   POINT (2.30267 48.84366)  007    A   small
1   POINT (7.25815 50.57581)  008    B  medium
2  POINT (15.43746 47.05842)  010    C     big

---

What I am looking for

I would like to create an empty GeoDataFrame (my_gdf = gpd.GeoDataFrame()), and then fill it directly in the for loop, without using the temporary list after the loop (my_gdf = gpd.GeoDataFrame(tmp_list))

I think that a row by row building would, in this case, have better performance. It would also allow me to use the id key from my_dict as the GeoDataFrame index, so that the result would be :

                     geometry  name    type
007   POINT (2.30267 48.84366)    A   small
008   POINT (7.25815 50.57581)    B  medium
010  POINT (15.43746 47.05842)    C     big

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

d = {'007': {'name': 'A', 'lat': 48.843664, 'lon': 2.302672, 'type': 'small' },
     '008': {'name': 'B', 'lat': 50.575813, 'lon': 7.258148, 'type': 'medium'},
     '010': {'name': 'C', 'lat': 47.058420, 'lon': 15.437464,'type': 'big'}}

## IN THE ABOVE CASE. Duration: ~1 ms (milisecond)
tmp_list = []
for item_key, item_value in d.items() :
    tmp_list.append({
      'geometry' : Point(item_value['lon'], item_value['lat']),
      'id': item_key,
      'name': item_value ['name'],
      'type': item_value ['type']
     })
gdf = gpd.GeoDataFrame(tmp_list)
##


## SOLUTION 1. Duration: ~2.3 ms, @gene's answer.
df = pd.DataFrame.from_dict(d, orient='index')
df["geometry"] = df.apply (lambda row: Point(row.lon,row.lat), axis=1)
gdf = gpd.GeoDataFrame(df, geometry=df.geometry)
##


## SOLUTION 2. Duration: ~2.5 ms
gdf = gpd.GeoDataFrame()    
gdf["id"]   = [k for k in d.keys()]
gdf["name"] = [d[k]["name"] for k in d.keys()]
gdf["type"] = [d[k]["type"] for k in d.keys()]
gdf["geometry"]  = [Point(d[k]["lon"], d[k]["lat"]) for k in d.keys()]    
gdf.set_index('id', inplace=True)
##


## SOLUTION 3. Duration: ~9.5 ms
gdf = gpd.GeoDataFrame(columns=["name", "type", "geometry"])
for k, v in d.items():
    gdf.loc[k] = (v["name"], v["type"], Point(v["lon"], v["lat"]))
##

print(gdf)

# OUTPUT for the last solution
#     name    type                   geometry
# 007    A   small   POINT (2.30267 48.84366)
# 008    B  medium   POINT (7.25815 50.57581)
# 010    C     big  POINT (15.43746 47.05842)

import pandas as pd
df = pd.DataFrame.from_dict(my_dict,orient='index')
print(df)
     name     lat        lon    type
007    A  48.843664   2.302672   small
008    B  50.575813   7.258148  medium
010    C  47.058420  15.437464     big
from shapely.geometry import Point
df["geometry"] = df.apply (lambda row: Point(row.lon,row.lat), axis=1)

gdf = gpd.GeoDataFrame(df, geometry=df.geometry)
print(gdf)
     name    lat        lon      type            geometry
007    A  48.843664   2.302672   small  POINT (2.302672 48.843664)
008    B  50.575813   7.258148  medium  POINT (7.258148 50.575813)
010    C  47.058420  15.437464     big  POINT (15.437464 47.05842)

gdf = gpd.GeoDataFrame(df, geometry=df.apply(lambda row: Point(row.lon,row.lat), axis=1)