Simple matplotlib errorbar plot/

errorbar_plot.py

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("./data/230116_Tumor_regression.csv")

# Group	Mouse	Day	Tumor(mm2)
# 0	G1	2210ES50_1	0	0.000000
# 1	G1	2210ES50_1	7	107.827200
# 2	G1	2210ES50_1	11	674.233875
# 3	G1	2210ES50_1	14	1573.768326
# 4	G1	2210ES50_1	18	3341.605256
# 5	G1	2210ES50_1	21	NaN
# 6	G1	2210ES50_1	25	NaN
# 7	G1	2210ES50_2	0	0.000000
# 8	G1	2210ES50_2	7	100.800000
# 9	G1	2210ES50_2	11	496.716748
# 10	G1	2210ES50_2	14	841.555000
# 11	G1	2210ES50_2	18	1405.689022
# 12	G1	2210ES50_2	21	2646.805230
# 13	G1	2210ES50_2	25	5637.610768
# 14	G1	2210ES50_3	0	0.000000
# 15	G1	2210ES50_3	7	107.681959
# 16	G1	2210ES50_3	11	500.273193
# 17	G1	2210ES50_3	14	1124.932500
# 18	G1	2210ES50_3	18	2096.455680
# 19	G1	2210ES50_3	21	3191.421303
# 20	G1	2210ES50_3	25	NaN
# 21	G4	2210ES50_22	0	0.000000
# 22	G4	2210ES50_22	7	109.263302
# 23	G4	2210ES50_22	11	162.636750
# 24	G4	2210ES50_22	14	429.359329
# 25	G4	2210ES50_22	18	720.147825
# 26	G4	2210ES50_22	21	1906.932632
# 27	G4	2210ES50_22	25	3553.364896
# 28	G4	2210ES50_23	0	0.000000
# 29	G4	2210ES50_23	7	102.136645
# 30	G4	2210ES50_23	11	305.984322
# 31	G4	2210ES50_23	14	445.383615
# 32	G4	2210ES50_23	18	1233.813600
# 33	G4	2210ES50_23	21	1877.068432
# 34	G4	2210ES50_23	25	3941.033324
# 35	G4	2210ES50_24	0	0.000000
# 36	G4	2210ES50_25	7	116.458545
# 37	G4	2210ES50_26	11	218.484000
# 38	G4	2210ES50_27	14	299.380752
# 39	G4	2210ES50_28	18	1230.631529
# 40	G4	2210ES50_29	21	2177.525467
# 41	G4	2210ES50_30	25	3898.437944

df_pivot = pd.pivot_table(
    df,
    index=["Group", "Day"],
    # columns = 'Day',
    values="Tumor(mm2)",
    aggfunc=[np.mean, np.std],
)

x = df_pivot.loc["G1"].index
y1 = df_pivot.loc["G1", "mean"].values.flatten()
y2 = df_pivot.loc["G4", "mean"].values.flatten()

yerr1 = df_pivot.loc["G1", "std"].values.flatten()
yerr2 = df_pivot.loc["G4", "std"].values.flatten()
# np.nan_to_num(yerr, copy=False)

plt.errorbar(x, y1, yerr=yerr1, fmt="o-", capsize=3.0, ecolor="k")
plt.errorbar(x, y2, yerr=yerr2, fmt="o-", capsize=3.0, ecolor="k")
plt.show()