Assign values with for loops to pandas DataFrame columns

Question

I am a Python beginner and have a problem with a for loop. I want to assign a list of numbers to different DataFrame columns. Manually, I can assign my values with the correct code, but copy and paste isn't a good style for programming.

The correct manual code looks like this:

df = pd.DataFrame(columns=['a', 'b', 'c'], index=range(100))
num = [100,200,300]
df['a'] = num[0]
df['b'] = num[1]
df['c'] = num[2]

df.head()
     a    b    c
0  100  200  300
1  100  200  300
2  100  200  300
3  100  200  300
4  100  200  300

My for loop is the following:

df = pd.DataFrame(columns=['a', 'b', 'c'], index=range(100))
for s in strings:
    for n in num:
        df[s] = n

df.head()

     a    b    c
0  300  300  300
1  300  300  300
2  300  300  300
3  300  300  300
4  300  300  300

Can anyone help me to write a for loop that works like my manual code?

Answer 1

If you already have an existing DataFrame, use assign :

df.assign(**dict(zip(df, num)))

---

You don't have to modify all columns if you don't need to!

df = pd.DataFrame(columns=['a', 'b', 'c', 'd', 'e'], index=range(100))
df.assign(**dict(zip(['a', 'c', 'e'], num))).head()

     a    b    c    d    e
0  100  NaN  200  NaN  300
1  100  NaN  200  NaN  300
2  100  NaN  200  NaN  300
3  100  NaN  200  NaN  300
4  100  NaN  200  NaN  300

Answer 2

The simplier is to pass a list to the DataFrame constructor, then no loop is necessary:

df = pd.DataFrame([[100,200,300]], columns=['a', 'b', 'c'], index=range(100))
print (df.head())
     a    b    c
0  100  200  300
1  100  200  300
2  100  200  300
3  100  200  300
4  100  200  300

But if you want a loop solution:

df = pd.DataFrame(columns=['a', 'b', 'c'], index=range(100))
num = [100,200,300]
cols = ['a','b','c']

for c, val in zip(cols, num):
    df[c] = val
print (df.head())
     a    b    c
0  100  200  300
1  100  200  300
2  100  200  300
3  100  200  300
4  100  200  300