我使用散景来绘制熊猫数据框。以下是代码：
map_options = GMapOptions(lat=19.075984, lng=72.877656, map_type="roadmap", zoom=11)
plot = GMapPlot(x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options)
plot.api_key = "xxxxx"
source = ColumnDataSource(
data=dict(
lat=[float(i) for i in data.lat],
lon=[float(i) for i in data.lon],
size=[int(i)/1000 for i in data['count']],
ID = [i for i in data.merchant_id],
Merchant = [str(i) for i in data.merchant_name],
count = [float(i) for i in data['count']]
)
)
hover = HoverTool(tooltips=[
("(x,y)", "($lat, $lon)"),
("ID", "$ID"),
("Name", "@Merchant"),
("count","$count")
])
# hover.renderers.append(circle_glyph)
plot.tools.append(hover)
circle = Circle(x="lon", y="lat", size='size', fill_color="blue", fill_alpha=0.8, line_color=None) …我有一个 pandas dataframe，我正在调用一个函数来在不满足条件的列中填充 NaN 。
以下是我的代码：
def clean_feedback(DF):
feed_id = DF.id_y.unique()
for ID in feed_id:
Min = np.argmin(np.abs(DF[DF.id_y == ID].created_at_x - DF[DF.id_y == ID].created_at_y))
print(Min)
DF[DF.id_y == ID].loc[DF[DF.id_y == ID].index != Min, 'comments'] = np.nan
return DF[DF.id_y == ID]
示例数据框是：
id_x user_id merchant_id amount_spent bill_number created_at_x checked_in chain_id id_y feedback_setting_id comments created_at_y updated_at feedback_type
1097 268868 975 42 149 None 2016-12-14 12:11:14 1 NaN 219 194 Lovely cafe! 2017-03-22 12:55:05 2017-10-05 06:45:49 1
2150 468876 975 42 278 None …