I am having trouble to convert my array of array to an array of string :
import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
I want to build a dataframe that would look like :
"coordinate"
0 '-1 -1'
1 '-2 -1'
2 '-3 -2'
3 '1 1'
4 '2 1'
5 '3 2'
Here are a few ways you can do this -
' '.join(i)data = [' '.join(str(i)) for i in X]
df = pd.DataFrame(data, columns=['coordinates'])
print(df)
coordinates
0 -1 -1
1 -2 -1
2 -3 -2
3 1 1
4 2 1
5 3 2
.astype(str)' '.join() over axis 1 to concatenate arraydata = np.apply_along_axis(' '.join, 1, X.astype(str))
df = pd.DataFrame(data, columns=['coordinates'])
print(df)
coordinates
0 -1 -1
1 -2 -1
2 -3 -2
3 1 1
4 2 1
5 3 2
You can do this with pandas as well.
df = pd.DataFrame(X)
df = df[0].map(str)+' '+df[1].map(str)
df = pd.DataFrame(df, columns=['coordinates'])
print(df)
coordinates
0 -1 -1
1 -2 -1
2 -3 -2
3 1 1
4 2 1
5 3 2
You can achieve this in the following manner:
import pandas as pd
import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
df = pd.DataFrame(columns=['coordinate'])
for index, item in enumerate(X):
df.at[index, 'coordinate'] = ' '.join(item.astype(str))
Results in:
print(df)
coordinate
0 -1 -1
1 -2 -1
2 -3 -2
3 1 1
4 2 1
5 3 2
You can use f-strings and list comprehension for example to do this task. For example:
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
X_string = np.array([f"{i[0]} {i[1]}" for i in X])
pd.DataFrame(data=X_string, columns=["coordinates"])
Output will be exactly the same as desired. But I think that this is not the best design for your task. If I were you I would likely split coordinates column into two separate (for example "lat" and "lon").
