以增量方式创建数据框

Question

I'm writing a code whose end result is a dataframe. This dataframe will be created on incremental basis. I read that the recommended approach to accomplish this is to create a list of list and at the end convert it into a dataframe. Below are major steps

dfColumns = ["ColA", "ColB", "ColC", "ColD"]
lst = []

for i in range(5):
    ColA = something
    ColB = something
    ColC = something
    ColD = something

    lst.append([ColA, ColB, ColC, ColD])

df = pd.DataFrame(lst, columns=dfColumns)

I am looking for a way such that I dont have to write ColA, ColB.... at 3 places. Is there a way to do something like this lst.append(dfColumns)

Answer 1

You can create a DataFrame from a list of dictionaries:

import pandas

column_names = ["ColA", "ColB", "ColC", "ColD"]
rows = []

for _ in range(5):

    # Explicitly create the row content
    row = {
        "ColA": "something",
        "ColB": "something",
        "ColC": "something",
        "ColD": "something",
    }

    # OR

    # Dynamically create each column from the column names
    row = {key: "something" for key in column_names}

    # Add the row to the list
    rows.append(row)


# Create a dataframe from a list of dicts will automatically find the column names
df = pandas.DataFrame(rows)