"""
This is a basic example of how to use the library to create a boxplot in Python
"""
from graphy2.core import Graphy
from graphy2.StyleSheet import BLUE_ON_WHITE_GRID
import seaborn as sns
if __name__ == "__main__":
# Load an example dataset from seaborn as the sample dataset
data = sns.load_dataset("tips")
# Modify a default style to have a smaller image size for a Non-print online only figure
BLUE_ON_WHITE_GRID["dpi"] = 72
# Call graphy2 to produce a box plot
Graphy(data, "Box Plot", BLUE_ON_WHITE_GRID).box_plot(x_var="day",
y_var="total_bill")
from graphy2.core import Graphy
if __name__ == '__main__':
# Set the directory where your images are stored
data = r"Path\To\Images"
# Set the size to bound your images too, and then the 3D position of the camera that will view your graph
Graphy(data, "Stacking Images").image_stack_figure(down_sampling=10,
elevation=15,
rotation=30)
from graphy2.core import Graphy
if __name__ == '__main__':
# Load in a csv with Labels, Amount, Explode columns
read_data = r"C:\Users\Samuel\PycharmProjects\graphy2\ExampleData\Pie.csv"
# Create the pie chart
Graphy(read_data, "Pie Plot").pie_chart(display_values='%1.1f%%')
if file_only:
return [file for file in os.listdir(directory) if os.path.isfile(f"{directory}/{file}")]
else:
return [file for file in os.listdir(directory)]
if __name__ == '__main__':
# read_data = r"C:\Users\Samuel\PycharmProjects\graphy2\ExampleData\Binary_meta_event_total.csv"
read_data = r"C:\Users\Samuel\PycharmProjects\AsthmaDisease\Testing"
for index, file in enumerate(directory_iterator(read_data)):
print(file)
a = Path(read_data, file)
if a.suffix == ".csv":
Graphy(f"{read_data}/{file}", f"A{index}").forest_plot()
# Graphy(f"{read_data}/base_forest.csv", "scarlet").forest_plot()
# Graphy(f"{read_data}/sc_cont.csv", "sc_cont").forest_plot()
# Graphy(f"{read_data}/sc_scarlet.csv", "sc_scarlet").forest_plot()
# Graphy(f"{read_data}/sci_cont.csv", "sci_cont").forest_plot()
# Graphy(f"{read_data}/sci_scarlet.csv", "sci_scarlet").forest_plot()
# Graphy(f"{read_data}/sci_int.csv", "sci_int").forest_plot()
# Graphy(f"{read_data}/sr_risk.csv", "sr_risk").forest_plot()
# Graphy(f"{read_data}/sr_scarlet.csv", "sr_scarlet").forest_plot()
# Graphy(f"{read_data}/sri_int.csv", "sri_int").forest_plot()
# Graphy(f"{read_data}/sri_scarlet.csv", "sri_scarlet").forest_plot()
# Graphy(f"{read_data}/sri_risk.csv", "sri_risk").forest_plot()
#
# Graphy(f"{read_data}/.csv", "AVbase_Forest").forest_plot()
"""
This is a basic example of how to use the library to create a violinplot in Python
"""
from graphy2.core import Graphy
if __name__ == "__main__":
import seaborn as sns
import os
# Load an example dataset from seaborn as the sample dataset
data = sns.load_dataset("tips")
# Get the path for the directory of this file, and save output to new sub-directory 'plots'
write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"plots")
# Call graphy2 to produce a box plot
Graphy(data, write_dir).violin_plot(x_var="day",
y_var="total_bill",
gradient_variable="sex")
from graphy2 import sys
from graphy2.core import Graphy
if __name__ == '__main__':
# Rgraphy2 Null args don't get passed as system arguments, but False will be passed as a string rather than as a
# bool so args needs formatting so that a False String returns a None type
args = []
for arg in sys.argv:
if "FALSE" in arg:
args.append(None)
else:
args.append(arg)
try:
function_name = args[1]
except IndexError as e:
raise Exception("No arguments passed to graphy_call.py") from e
try:
class_args = [args[i] for i in range(2, 6)]
except IndexError as e:
raise Exception("Not enough arguments passed to graphy_call.py for the class args. Args should be:\n"
"[0]Script_name\n[1]class_method_name\n[2]path_to_data_file\n[3]write_directory\n"
"[4]figure_name\n[5]style_sheet\n[6+]args for class_method_name")
method_args = [args[i] for i in range(6, len(args))]
getattr(Graphy(*class_args), str(function_name))(*method_args)
"""
This is a basic example of how to use the library to create a lineplot in Python
"""
from graphy2.core import Graphy
import seaborn as sns
if __name__ == "__main__":
# Load an example dataset from seaborn as the sample dataset
data = sns.load_dataset("fmri")
# Call graphy2 to produce a line plot
Graphy(data, "Line Plot").line_plot(x_var="timepoint", y_var="signal")
"""
This is a basic example of how to use the library to create a kdeplot in Python
"""
from graphy2.core import Graphy
import numpy as np
np.random.seed(10)
import pandas as pd
if __name__ == "__main__":
import seaborn as sns
import os
# Load an example dataset from seaborn as the sample dataset
mean, cov = [0, 2], [(1, .5), (.5, 1)]
x, y = np.random.multivariate_normal(mean, cov, size=50).T
data = pd.DataFrame({'X': x, 'Y': y}, columns=['X', 'Y'])
# Get the path for the directory of this file, and save output to new sub-directory 'plots'
write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"plots")
# Call graphy2 to produce a box plot
Graphy(data, write_dir).kde_plot()
"""
This is a basic example of how to use the library natively in python.
"""
from graphy2.core import Graphy
if __name__ == "__main__":
# Set the file path
csv_path = "./Path/to/your/file.csv"
# Set where to save your file
write_dir = "./Save/Directory"
# Call graphy2's Graphy for the graph you want
Graphy(csv_path, write_dir).scatter_plot("carat", "price", "clarity",
"depth")
"""
This is a basic example of how to use the library to create a barplot in Python
"""
from graphy2.core import Graphy
if __name__ == "__main__":
import seaborn as sns
import os
# Load an example dataset from seaborn as the sample dataset
data = sns.load_dataset("tips")
# Get the path for the directory of this file, and save output to new sub-directory 'plots'
write_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"plots")
# Call graphy2 to produce a box plot
Graphy(data, write_dir).bar_plot(x_var="sex",
y_var="total_bill",
gradient_variable="smoker")