CODEWITHSUNDEEP
pythonpandas
user6074035
user6074035

Reputation: 107

Populating pandas dataframe with int - TypeError

I want to populate a pandas dataframe with a integer called delay time. When I do the below, I am getting an error as below also.

train_df = pd.DataFrame("Train_Number", "Start_Station", "Stop_Station", "Delay_Time") 

for i in range(1,25): 
    train_df = train_df.append(i, "Dublin", "Belfast", 0)

Error: TypeError: data type 'Delay_Time' not understood

I have tried changing 0 to int(0), np.zeros(), but neither worked.

What am I doing wrong?

Upvotes: 1

Views: 31

Answers (1)

jezrael
jezrael

Reputation: 862406

For performance reason create list of tuples first and then call DataFrame constructor:

L = []
for i in range(1,25): 
   L.append((i, "Dublin", "Belfast", 0))

Or use list comprehension:

L = [(i, "Dublin", "Belfast", 0) for i in range(1,25)]

cols = ["Train_Number", "Start_Station", "Stop_Station", "Delay_Time"]
train_df = pd.DataFrame(L, columns=cols) 

print (train_df)
    Train_Number Start_Station Stop_Station  Delay_Time
0              1        Dublin      Belfast           0
1              2        Dublin      Belfast           0
2              3        Dublin      Belfast           0
3              4        Dublin      Belfast           0
4              5        Dublin      Belfast           0
5              6        Dublin      Belfast           0
6              7        Dublin      Belfast           0
7              8        Dublin      Belfast           0
8              9        Dublin      Belfast           0
9             10        Dublin      Belfast           0
10            11        Dublin      Belfast           0
11            12        Dublin      Belfast           0
12            13        Dublin      Belfast           0
13            14        Dublin      Belfast           0
14            15        Dublin      Belfast           0
15            16        Dublin      Belfast           0
16            17        Dublin      Belfast           0
17            18        Dublin      Belfast           0
18            19        Dublin      Belfast           0
19            20        Dublin      Belfast           0
20            21        Dublin      Belfast           0
21            22        Dublin      Belfast           0
22            23        Dublin      Belfast           0
23            24        Dublin      Belfast           0

Upvotes: 1

Related Questions