Combining 4 sets of data in python
Question:
I have four separate sets of data for each of the 4 quarters in the year, the columns are identical within all. What is a python function I can use to combine them into one master data set?
Thank you!
Answers:
You could use pandas dataframes. It would look something like this.
Depends on how the data looks. But atleast take a look at pandas, well documented. In concat you might need to care for the index
import pandas as pd
set1 = pd.DataFrame(set1)
set2 = pd.DataFrame(set2)
set3 = pd.DataFrame(set3)
master_set = pd.concat(set1, set2, set3)
You want to use the pandas concat funtion for this since the dataframes are identical. See this example:
df1 = pd.DataFrame(
{
"A": ["A0", "A1", "A2", "A3"],
"B": ["B0", "B1", "B2", "B3"],
"C": ["C0", "C1", "C2", "C3"],
"D": ["D0", "D1", "D2", "D3"],
},
index=[0, 1, 2, 3],
)
df2 = pd.DataFrame(
{
"A": ["A4", "A5", "A6", "A7"],
"B": ["B4", "B5", "B6", "B7"],
"C": ["C4", "C5", "C6", "C7"],
"D": ["D4", "D5", "D6", "D7"],
},
index=[4, 5, 6, 7],
)
df3 = pd.DataFrame(
{
"A": ["A8", "A9", "A10", "A11"],
"B": ["B8", "B9", "B10", "B11"],
"C": ["C8", "C9", "C10", "C11"],
"D": ["D8", "D9", "D10", "D11"],
},
index=[8, 9, 10, 11],
)
frames = [df1, df2, df3]
result = pd.concat(frames)
I have four separate sets of data for each of the 4 quarters in the year, the columns are identical within all. What is a python function I can use to combine them into one master data set?
Thank you!
You could use pandas dataframes. It would look something like this.
Depends on how the data looks. But atleast take a look at pandas, well documented. In concat you might need to care for the index
import pandas as pd
set1 = pd.DataFrame(set1)
set2 = pd.DataFrame(set2)
set3 = pd.DataFrame(set3)
master_set = pd.concat(set1, set2, set3)
You want to use the pandas concat funtion for this since the dataframes are identical. See this example:
df1 = pd.DataFrame(
{
"A": ["A0", "A1", "A2", "A3"],
"B": ["B0", "B1", "B2", "B3"],
"C": ["C0", "C1", "C2", "C3"],
"D": ["D0", "D1", "D2", "D3"],
},
index=[0, 1, 2, 3],
)
df2 = pd.DataFrame(
{
"A": ["A4", "A5", "A6", "A7"],
"B": ["B4", "B5", "B6", "B7"],
"C": ["C4", "C5", "C6", "C7"],
"D": ["D4", "D5", "D6", "D7"],
},
index=[4, 5, 6, 7],
)
df3 = pd.DataFrame(
{
"A": ["A8", "A9", "A10", "A11"],
"B": ["B8", "B9", "B10", "B11"],
"C": ["C8", "C9", "C10", "C11"],
"D": ["D8", "D9", "D10", "D11"],
},
index=[8, 9, 10, 11],
)
frames = [df1, df2, df3]
result = pd.concat(frames)