In [1]:
import pandas as pd
import numpy as np
In [2]:
df = pd.read_csv("ZebraBotswana.txt")
In [3]:
print(df.shape)

(53776, 4)

The dataset contains 53776 records, with 4 columns.

In [4]:
print(df.columns)

Index(['UnixTime', 'Lng', 'Lat', 'Animal'], dtype='object')
In [5]:
print(df.head())

       UnixTime        Lng        Lat Animal
0  1.193263e+09  23.523616 -19.391531  Z3864
1  1.193267e+09  23.523497 -19.391684  Z3864
2  1.193270e+09  23.523463 -19.391651  Z3864
3  1.193274e+09  23.523425 -19.391645  Z3864
4  1.193278e+09  23.523434 -19.391541  Z3864
In [6]:
animals = np.unique(df["Animal"])
print(animals)

['Z3743' 'Z3864' 'Z3866' 'Z6399' 'Z6402' 'Z6405' 'Z6407']

We calculate the day (integer) corresponding to each Unix timestamp by dividing the Unix timestamp by 24 times 60 times 60.

In [7]:
df["day"] = df["UnixTime"].map(lambda x: int(x/(24.*60.*60.)))
print(df.head())

       UnixTime        Lng        Lat Animal    day
0  1.193263e+09  23.523616 -19.391531  Z3864  13810
1  1.193267e+09  23.523497 -19.391684  Z3864  13810
2  1.193270e+09  23.523463 -19.391651  Z3864  13811
3  1.193274e+09  23.523425 -19.391645  Z3864  13811
4  1.193278e+09  23.523434 -19.391541  Z3864  13811
In [8]:
lat_to_dist = 111.3 # distance in km of a degree in longitude
lng_to_dist = 104.6 # distance in km of a degree in latitude
In [9]:
for animal in animals:
    df_animal = df[df["Animal"]==animal].copy()
    lng = np.array(df_animal["Lng"])
    lat = np.array(df_animal["Lat"])
    dlng = (lng[1:]-lng[:-1])*lng_to_dist
    dlat = (lat[1:]-lat[:-1])*lat_to_dist
    dist = (dlng**2+dlat**2)**0.5
    df_animal["dist"] = np.hstack([0,dist]) # Adding the missing element due to distancing
    daily_distance = df_animal.groupby(["day"]).sum()["dist"]
    print(animal)
    print("Avg. daily distance:    %5.2f+/-%5.2f km"%(daily_distance.mean(),daily_distance.std()))
    print("Min/Max daily distance: %5.2f km / %5.2f km"%(daily_distance.min(),daily_distance.max()))

Z3743
Avg. daily distance:    12.23+/- 9.03 km
Min/Max daily distance:  0.24 km / 57.76 km
Z3864
Avg. daily distance:    15.50+/-11.22 km
Min/Max daily distance:  0.02 km / 52.74 km
Z3866
Avg. daily distance:    11.25+/- 6.76 km
Min/Max daily distance:  2.51 km / 56.76 km
Z6399
Avg. daily distance:    13.78+/- 9.10 km
Min/Max daily distance:  1.22 km / 75.40 km
Z6402
Avg. daily distance:    12.38+/- 7.20 km
Min/Max daily distance:  0.38 km / 51.02 km
Z6405
Avg. daily distance:    11.68+/- 7.04 km
Min/Max daily distance:  2.53 km / 53.59 km
Z6407
Avg. daily distance:    12.45+/- 7.15 km
Min/Max daily distance:  0.17 km / 51.31 km
In [ ]: