import numpy as np
import pandas as pd

# Create an empty DataFrame with 5 columns
df = pd.DataFrame(columns=['col1', 'col2', 'col3', 'col4', 'col5'])  # Or any column names you want

# Method 1: Using a dictionary and append (less efficient for large DataFrames)
for _ in range(5):  # Add 5 rows
    df = pd.concat([df, pd.DataFrame([{'col1': np.nan, 'col2': np.nan, 'col3': np.nan, 'col4': np.nan, 'col5': np.nan}])], ignore_index=True)
d =  {"col1": "ta", "col2": "gs"}
df.loc[1, "col1"] = d["col1"]
for index, row in enumerate(df):
    print(index)