I have a dataframe storing information of 4 subjects A, B, C, D.
<code>df = pd.DataFrame({
'subject': ['A', 'B', 'C', 'D'],
'X1': [80, 90, 70, 60],
'Y1': [10, 25, 20, 15],
'X2': [63, 75, 84, 92],
'Y2': [13, 28, 25, 18],
'X3': [36, 78, 64, 82],
'Y3': [18, 25, 24, 16]
})
print(df)
</code>
<code>df = pd.DataFrame({
'subject': ['A', 'B', 'C', 'D'],
'X1': [80, 90, 70, 60],
'Y1': [10, 25, 20, 15],
'X2': [63, 75, 84, 92],
'Y2': [13, 28, 25, 18],
'X3': [36, 78, 64, 82],
'Y3': [18, 25, 24, 16]
})
print(df)
</code>
df = pd.DataFrame({
'subject': ['A', 'B', 'C', 'D'],
'X1': [80, 90, 70, 60],
'Y1': [10, 25, 20, 15],
'X2': [63, 75, 84, 92],
'Y2': [13, 28, 25, 18],
'X3': [36, 78, 64, 82],
'Y3': [18, 25, 24, 16]
})
print(df)
From the above data frame, I want to create 4 data frames df_A, df_B, df_C and df_D such that the new data frame has x1, y1 as the first row, x2, y2 as second and x3, y3 as third.
Expects output data frames are
<code>df_A = pd.DataFrame({
'X': [80, 63, 36],
'Y': [10, 13, 18]
})
print(df_A)
df_B = pd.DataFrame({
'X': [90, 75, 78],
'Y': [25, 28, 25]
})
print(df_B)
df_C = pd.DataFrame({
'X': [70, 84, 64],
'Y': [20, 25, 24]
})
print(df_C)
df_D = pd.DataFrame({
'X': [60, 92, 82],
'Y': [15, 18, 16]
})
print(df_D)
</code>
<code>df_A = pd.DataFrame({
'X': [80, 63, 36],
'Y': [10, 13, 18]
})
print(df_A)
df_B = pd.DataFrame({
'X': [90, 75, 78],
'Y': [25, 28, 25]
})
print(df_B)
df_C = pd.DataFrame({
'X': [70, 84, 64],
'Y': [20, 25, 24]
})
print(df_C)
df_D = pd.DataFrame({
'X': [60, 92, 82],
'Y': [15, 18, 16]
})
print(df_D)
</code>
df_A = pd.DataFrame({
'X': [80, 63, 36],
'Y': [10, 13, 18]
})
print(df_A)
df_B = pd.DataFrame({
'X': [90, 75, 78],
'Y': [25, 28, 25]
})
print(df_B)
df_C = pd.DataFrame({
'X': [70, 84, 64],
'Y': [20, 25, 24]
})
print(df_C)
df_D = pd.DataFrame({
'X': [60, 92, 82],
'Y': [15, 18, 16]
})
print(df_D)
How do I achieve this? I tried with iloc but failed.