import pandas as pd

df = pd.read_csv("daten.csv",
delimiter=";",
na_values=["."],
index_col="ID",
encoding="utf-8")


df2 = df.sort_values(["Größe", "ID"])

# df3 = df.drop([80,90])
# df4 = df.drop(columns=["Raucher", "Blutgruppe"])


df3 = df2[df2["Größe"] > 175]

# elems = df2.loc[[10], "Blutgruppe":"Größe"]
# elems = df2.iloc[0:3, 0:2]
# elems = df2.loc[20:80,"Geschlecht":"Raucher"]

print(df2)

# print("")
# print(f"Type: {type(elems)}")
# print(elems)

# print(df2.index)
# df5 = df2.set_index("Alter", append=True)
df5 = df2.set_index(["Alter", "Geschlecht"], append=True)
# print(df5)
# print(df5.index)

rowsIter = df.iterrows()
colsIter = df.items()

# print("Befor row loop:\n")
# for rowLabel, row in rowsIter:
#     print(f"Label: {type(rowLabel)}, row: {type(row)}")
#     print(f"{rowLabel}:\n{row}\n")

# print("Befor col loop:\n")
# for colLabel, col in colsIter:
#     print(f"Label: {type(colLabel)}, Col: {type(col)}")
#     print(f"{colLabel}:\n{col}\n")

# print("\n")
# nextCol = next(colsIter)
# nextColLabel = nextCol[0]
# nextColSeries = nextCol[1]

# print(f"Label: {nextColLabel}")
# print(f"Series:\n{nextColSeries}")

# seriesIter = nextColSeries.items()
# nextElem = next(seriesIter)

# print(nextElem)
print(df2)
df7 = df2.fillna(0)
# print(df7)

print(df)
meanRet = df.max()
print(type(meanRet))
print(meanRet)