基于位置坐标的叶片热图递归误差

时间:2019-03-17 18:25:09

标签: recursion heatmap folium

我正在尝试使用我的数据绘制大叶热图。以下是我的代码,但我不断收到错误消息:RecursionError: maximum recursion depth exceeded,我不知道这是什么意思。有输入吗?下面是热图的代码。

# Creating a dataframe of the 'month', 'day_of_week' and 'location' day_month = pd.DataFrame(df_criclean[['month', 'day_of_week','location']])
day_month.sort_values('month', ascending = False).head(10)

# Trying to use folium to make a heatmap of the data I have in 'day_month'

map = folium.Map(location=[42.3601, -71.0589], [enter image description here][1]tiles='cartodbpositron', zoom_start=1)
HeatMap(day_month['location']).add_to(map)

5 个答案:

答案 0 :(得分:0)

我也有这个“ bug” ,我认为它与变量类型为object而不是float64或其他基本类型有关(我的数据集有很多""而不是有效的GPS坐标)。

#> ./folium-test.py 
--------------------
                                    _id city daily_rain                date  ... wind_degrees wind_dir wind_speed wind_string
0  {'$oid': '5571aaa8e4b07aa3c1c4e231'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN        4.8         NaN
1  {'$oid': '5571aaa9e4b07aa3c1c4e232'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN        1.6         NaN
2  {'$oid': '5571aaa9e4b07aa3c1c4e233'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN       11.3         NaN
3  {'$oid': '5571aaa9e4b07aa3c1c4e234'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN         13         NaN
4  {'$oid': '5571aaa9e4b07aa3c1c4e235'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN          5         NaN

[5 rows x 18 columns]
(500, 18)
--------------------
0      8.48402346662349
1      8.15408706665039
2      9.81855869293213
3      9.83495235443115
4      9.92164134979248
5      9.26684331789147
6      9.59504252663464
7      9.07091170549393
8      8.99822786450386
9       8.9606299996376
10     8.93120750784874
11     9.02073669538368
12             8.912937
13                     
             ...       
498            8.912937
499                    
Name: longitudine, Length: 500, dtype: object
0      44.3720632234234
1      43.9720632409982
2      44.1090045985169
3      44.1142735479457
4       44.145446252325
5      44.3377021234296
6      44.3773853328621
7      44.3798960485217
8      44.4051013957662
9      44.4094088501931
10     44.4160476104163
11     44.4527250625144
12            44.516321
13                     
             ...       
498           44.516321
499                    
Name: latitudine, Length: 500, dtype: object
Traceback (most recent call last):
  File "./folium-test.py", line 89, in <module>
    folium.Marker([row["latitudine"], row["longitudine"]], popup=row["temperatura"]).add_to(marker_cluster)
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/map.py", line 258, in __init__
    self.location = _validate_coordinates(location)
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 53, in _validate_coordinates
    if _isnan(coordinates):
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 79, in _isnan
    return any(math.isnan(value) for value in _flatten(values))
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 79, in <genexpr>
    return any(math.isnan(value) for value in _flatten(values))
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 71, in _flatten
    for j in _flatten(i):
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 71, in _flatten
    for j in _flatten(i):
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 71, in _flatten
    for j in _flatten(i):
  [Previous line repeated 982 more times]
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 70, in _flatten
    if _is_sized_iterable(i):
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/site-packages/folium/utilities.py", line 32, in _is_sized_iterable
    return isinstance(arg, abc.Sized) & isinstance(arg, abc.Iterable)
  File "/mnt/ros-data/venvs/meteo-viz/lib/python3.7/abc.py", line 139, in __instancecheck__
    return _abc_instancecheck(cls, instance)
RecursionError: maximum recursion depth exceeded in comparison

但是,如果我将这些行添加到代码中,folium可以很好地工作(即使对于大型数据集):

df['longitudine'] = df['longitudine'].replace(r'\s+', np.nan, regex=True)
df['longitudine'] = df['longitudine'].replace(r'^$', np.nan, regex=True)
df['longitudine'] = df['longitudine'].fillna(-0.99999)
df['longitudine'] = pd.to_numeric(df['longitudine'])
df['latitudine'] = df['latitudine'].replace(r'\s+', np.nan, regex=True)
df['latitudine'] = df['latitudine'].replace(r'^$', np.nan, regex=True)
df['latitudine'] = df['latitudine'].fillna(-0.99999)
df['latitudine'] = pd.to_numeric(df['latitudine'])

这是输出:

#> ./folium-test.py 
--------------------
                                    _id city daily_rain                date  ... wind_degrees wind_dir  wind_speed  wind_string
0  {'$oid': '5571aaa8e4b07aa3c1c4e231'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN         4.8          NaN
1  {'$oid': '5571aaa9e4b07aa3c1c4e232'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN         1.6          NaN
2  {'$oid': '5571aaa9e4b07aa3c1c4e233'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN        11.3          NaN
3  {'$oid': '5571aaa9e4b07aa3c1c4e234'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN          13          NaN
4  {'$oid': '5571aaa9e4b07aa3c1c4e235'}  NaN          0 2015-06-05 15:56:00  ...          NaN      NaN           5          NaN

[5 rows x 18 columns]
(500, 18)
--------------------
0      8.484023
1      8.154087
2      9.818559
3      9.834952
4      9.921641
5      9.266843
6      9.595043
7      9.070912
8      8.998228
9      8.960630
10     8.931208
11     9.020737
12     8.912937
13    -0.999990
         ...   
498    8.912937
499   -0.999990
Name: longitudine, Length: 500, dtype: float64
0      44.372063
1      43.972063
2      44.109005
3      44.114274
4      44.145446
5      44.337702
6      44.377385
7      44.379896
8      44.405101
9      44.409409
10     44.416048
11     44.452725
12     44.516321
13     -0.999990
         ...    
498    44.516321
499    -0.999990
Name: latitudine, Length: 500, dtype: float64
1 43.9720632409982 8.154087066650389 30.6

答案 1 :(得分:0)

# These are the top 20 'coordinates' according to the data.

sns.set(font_scale=1.25)
f, ax = plt.subplots(figsize=(15,8))
sns.countplot(y='location', data=df_criclean, order=df_criclean.location.value_counts().iloc[:20].index)



# Here, I'm making a Dataframe of the locations and the count.  What you see below
# is the top 5 locations. 
# I want to use this for my folium map.

df1 = df_criclean.groupby(["lat", "long", "location"]).size().reset_index(name='count')
df1['location'] = df1['location'].str.replace(',', '')

# Sort the count from highest count with location to lowest.
print(df1.sort_values(by = 'count', ascending=False).head())

# The DataFrame not sorted.
print(df1.head())

# convert to (n, 2) nd-array format for heatmap

locationArr = df1[['lat', 'long']].as_matrix()

m = folium.Map(location=[42.32, -71.0589], zoom_start=12)
m.add_child(plugins.HeatMap(locationArr, radius=9))
m`

答案 2 :(得分:0)

我遇到了同样的问题,并通过将我的纬度和经度值转换为浮点数来解决它:

import folium
import numpy as np

plot = folium.Map(location=[40, -95], zoom_start=4)

coords = np.random.rand(1000,2) * 100

for lat, lon in coords:
  folium.Circle(location=[float(lat), float(lon)]).add_to(plot)

答案 3 :(得分:0)

我遇到了同样的错误,直到我将坐标从 str 转换为 float

df['lat'] = df['lat'].astype(float).fillna(0)
df['long'] = df['long'].astype(float).fillna(0)

答案 4 :(得分:0)

我遇到了同样的问题。我必须使用 .to_numpy() 方法将其转换为 numpy 数组才能使其工作。