I just met this question,and I find it is the NaN in my data,when I fillna(method="ffill"),it becomes normal.
for file in file_list:
data = pd.read_csv("C:/data/future/day/"+file)
datetime_list=list(data['datetime'])
begin_date=datetime_list[0]
if begin_date>"2010-01-01":
end_date=datetime_list[-1]
df1=df[df['datetime']>=begin_date]
df1=df1[df1['datetime']<=end_date]
if len(df1)!=len(data):
print(file)
df1=df1[['datetime']]
df1.index=range(len(df1))
# df2=pd.concat([df1,data],join="outer",keys="datetime",axis=1)
df2=pd.merge(df1,data,on='datetime',how='outer')
df2=df2.fillna(method="ffill")
df2.to_csv("C:/data/future/day/"+file,index=False)
