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plot_invasiveness.py
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import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
total_data = pd.read_csv("../Downloads/CAF Media Dataset(TOTALNUMBERS).csv")
total_data.plot()
pdo_01 = pd.read_csv("../Downloads/CAF Media Dataset(PDO1).csv").drop(0)
pdo_02 = pd.read_csv("../Downloads/CAF Media Dataset(PDO2).csv").drop(0)
pdo_03 = pd.read_csv("../Downloads/CAF Media Dataset(PDO3).csv").drop(0)
pdo_04 = pd.read_csv("../Downloads/CAF Media Dataset(PDO4 (non-sig)).csv").drop(0)
pdo_05 = pd.read_csv("../Downloads/CAF Media Dataset(PDO5).csv").drop(0)
pdo_06 = pd.read_csv("../Downloads/CAF Media Dataset(PDO6).csv").drop(0)
pdo_07 = pd.read_csv("../Downloads/CAF Media Dataset(PDO7).csv").drop(0)
pdo_08 = pd.read_csv("../Downloads/CAF Media Dataset(PDO8).csv").drop(0)
pdo_09 = pd.read_csv("../Downloads/CAF Media Dataset(PDO9).csv").drop(0)
pdo_10 = pd.read_csv("../Downloads/CAF Media Dataset(PDO10).csv").drop(0)
pdo_11 = pd.read_csv("../Downloads/CAF Media Dataset(PDO11 (non-sig)).csv").drop(0)
pdo_12 = pd.read_csv("../Downloads/CAF Media Dataset(PDO12).csv").drop(0)
pdo_13 = pd.read_csv("../Downloads/CAF Media Dataset(PDO13).csv").drop(0)
pdo_14 = pd.read_csv("../Downloads/CAF Media Dataset(PDO14).csv").drop(0)
pdo_15 = pd.read_csv("../Downloads/CAF Media Dataset(PDO15).csv").drop(0)
all_pdo = [
pdo_01,
pdo_02,
pdo_03,
pdo_04,
pdo_05,
pdo_06,
pdo_07,
pdo_08,
pdo_09,
pdo_10,
pdo_11,
pdo_12,
pdo_13,
pdo_14,
pdo_15,
]
column_names = [
"Control",
"myCAF",
"iCAF",
"Control (1/circularity)",
"myCAF (1/circularity)",
"iCAF (1/circularity)",
]
for pdo in all_pdo:
pdo.columns = column_names
plt, ax = plt.subplots()
total_data[total_data["Condition"] == "CONTROL"].plot(kind="box", ax=ax).set_title(
"CONTROL"
)
total_data[total_data["Condition"] == "MyCAF"].plot(kind="box", ax=ax).set_title(
"MyCAF"
)
total_data[total_data["Condition"] == "iCAF "].plot(kind="box").set_title("iCAF")
pdo_ic = pd.read_csv("../inverse_circularity_pdo.csv")
sns.catplot(data=pdo_ic, x="condition", y="(1/circularity)")
rownames = list(total_data["Unnamed: 0"])
conditions = list()
for row in rownames:
conditions.append(row.split("-")[1])
total_data["Condition"] = conditions
import seaborn as sns
sns.catplot(data=all_pdo[0], y=["Control (1/circularity)"])