<filename>down_left_point.py<gh_stars>1-10
import pandas as pd
import numpy as np
from auxiliaryfunctions import *

df=pd.read_pickle('final_cleaned.df')
#df.to_csv('final_cleaned.csv')
df_2 = pd.DataFrame(columns=['lon','the', 'timestamp_longitude_latitude'])
df_3 = pd.DataFrame(columns=['lat','the', 'timestamp_longitude_latitude'])

#lst=[]
the_lst_lon=[]
the_lst_lat=[]

for index, row in df.iterrows():
    lst=df['timestamp_longitude_latitude'].iloc[index]
    min_lon=lst[0][1]
    min_lat=lst[0][2]
    the_lon=str(lst[0][1])+',' +str(lst[0][2])
    the_lat=str(lst[0][1])+',' +str(lst[0][2])
    for i in range(len(lst)):
        temp_lon=lst[i][1]
        temp_lat=lst[i][2]
        if temp_lon<min_lon :
            min_lon=temp_lon
            the_lon=str(lst[i][1])+',' +str(lst[i][2]) #the leftest diadromi point
            the_lst_lon=lst
        if temp_lat<min_lat :
            min_lat=temp_lat
            the_lat=str(lst[i][1])+',' +str(lst[i][2])
            the_lst_lat=lst

    #df_2=df_2.append({'lon': str(min_lon), 'the': the_lon, 'timestamp_longitude_latitude': the_lst_lon}, ignore_index=True)
    #df_3=df_3.append({'lat': str(min_lat), 'the': the_lat, 'timestamp_longitude_latitude': the_lst_lat}, ignore_index=True)
    df_2=df_2.append({'lon': str(min_lon)}, ignore_index=True)
    df_3=df_3.append({'lat': str(min_lat)}, ignore_index=True)
    

df_2=df_2.sort_values(by=['lon'], ascending=False) 
df_3=df_3.sort_values(by=['lat'])


downleft_lon = df_2['lon'].iloc[0]
downleft_lat = df_3['lat'].iloc[0]

print downleft_lon
print downleft_lat


<filename>down_left_point.py<gh_stars>1-10
import pandas as pd
import numpy as np
from auxiliaryfunctions import *

df=pd.read_pickle('final_cleaned.df')
#df.to_csv('final_cleaned.csv')
df_2 = pd.DataFrame(columns=['lon','the', 'timestamp_longitude_latitude'])
df_3 = pd.DataFrame(columns=['lat','the', 'timestamp_longitude_latitude'])

#lst=[]
the_lst_lon=[]
the_lst_lat=[]

for index, row in df.iterrows():
    lst=df['timestamp_longitude_latitude'].iloc[index]
    min_lon=lst[0][1]
    min_lat=lst[0][2]
    the_lon=str(lst[0][1])+',' +str(lst[0][2])
    the_lat=str(lst[0][1])+',' +str(lst[0][2])
    for i in range(len(lst)):
        temp_lon=lst[i][1]
        temp_lat=lst[i][2]
        if temp_lon<min_lon :
            min_lon=temp_lon
            the_lon=str(lst[i][1])+',' +str(lst[i][2]) #the leftest diadromi point
            the_lst_lon=lst
        if temp_lat<min_lat :
            min_lat=temp_lat
            the_lat=str(lst[i][1])+',' +str(lst[i][2])
            the_lst_lat=lst

    #df_2=df_2.append({'lon': str(min_lon), 'the': the_lon, 'timestamp_longitude_latitude': the_lst_lon}, ignore_index=True)
    #df_3=df_3.append({'lat': str(min_lat), 'the': the_lat, 'timestamp_longitude_latitude': the_lst_lat}, ignore_index=True)
    df_2=df_2.append({'lon': str(min_lon)}, ignore_index=True)
    df_3=df_3.append({'lat': str(min_lat)}, ignore_index=True)
    

df_2=df_2.sort_values(by=['lon'], ascending=False) 
df_3=df_3.sort_values(by=['lat'])


downleft_lon = df_2['lon'].iloc[0]
downleft_lat = df_3['lat'].iloc[0]

print downleft_lon
print downleft_lat


#df.to_csv('final_cleaned.csv') #lst=[] #the leftest diadromi point #df_2=df_2.append({'lon': str(min_lon), 'the': the_lon, 'timestamp_longitude_latitude': the_lst_lon}, ignore_index=True) #df_3=df_3.append({'lat': str(min_lat), 'the': the_lat, 'timestamp_longitude_latitude': the_lst_lat}, ignore_index=True)