View read_data_gmplot.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
import gmplot | |
data = pd.read_csv('3D_spatial_network.csv') | |
data.head() |
View scatter-plot-gmplot.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# latitude and longitude list | |
latitude_list = data['LATITUDE'] | |
longitude_list = data['LONGITUDE'] | |
# center co-ordinates of the map | |
gmap = gmplot.GoogleMapPlotter( 56.730876,9.349849,9) | |
# plot the co-ordinates on the google map | |
gmap.scatter( latitude_list, longitude_list, '# FF0000', size = 40, marker = True) |
View category_encoders_dataframe.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
import category_encoders as ce | |
# create a Dataframe | |
data = pd.DataFrame({ 'gender' : ['Male', 'Female', 'Male', 'Female', 'Female'], | |
'class' : ['A','B','C','D','A'], | |
'city' : ['Delhi','Gurugram','Delhi','Delhi','Gurugram'] }) | |
data.head() |
View encodeda_data.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# One Hot Encoding | |
# create an object of the One Hot Encoder | |
ce_OHE = ce.OneHotEncoder(cols=['gender','city']) | |
# transform the data | |
data = ce_OHE.fit_transform(data) | |
data.head() |
View progress_apply_data.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
from tqdm._tqdm_notebook import tqdm_notebook | |
from pysal.lib.cg import harcdist | |
tqdm_notebook.pandas() | |
data = pd.read_csv('3D_spatial_network.csv') | |
data.head() |
View calculate_distance.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# calculate the distance of each data point from # (Latitude, Longitude) = (58.4442, 9.3722) | |
def calculate_distance(x): | |
return harcdist((x['LATITUDE'],x['LONGITUDE']),(58.4442, 9.3722)) | |
data['DISTANCE'] = data.progress_apply(calculate_distance,axis=1) |
View pandas_profiling.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
import pandas_profiling | |
# read the dataset | |
data = pd.read_csv('add-your-data-here') | |
pandas_profiling.ProfileReport(data) |
View read_time_series_data.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
data = pd.read_excel('sales-data.xlsx') | |
data.head() |
View convert_data_time.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
data['date'] = pd.to_datetime(data['date']) |
View resample-data.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
data.set_index('date').groupby('name')["ext price"].resample("M").sum() |
OlderNewer