Effects of investment environment on SME's gross capital formation in the Sub-Saharan region
Abstract
1.Introduction
2 Literature Review
3. Methodology
Data
Methods
4.Data Pre-processing and Exploration
0
All Countries
14.2
1
East Asia & Pacific
13.6
2
Europe & Central Asia
9.4
3
Latin America & Caribbean
9
4
Middle East & North Africa
12.1
5
South Asia
12.1
6
Sub-Saharan Africa
23.9
7
Afghanistan
12.1
8
Albania
3.1
9
Angola
13.1
19
Burkina Faso
21.73910482
33
Botswana
27.31825419
46
Comoros
14.86809293
72
Ethiopia
34.72881719
80
Gabon
19.25823243
83
Ghana
22.64933551
121
Kenya
19.37598625
141
Lesotho
22.98425475
158
Mali
20.4583026
165
Mozambique
50.0478227
111
Nigeria
30.2
142
Tanzania
37.9
148
Tunisia
39.4
150
Uganda
12.3
159
Zambia
31.1
160
Zimbabwe
20.6
25
Botswana
3.9
28
Burkina Faso
6.8
55
Ethiopia
9.9
59
Gabon
6.5
63
Ghana
6.6
81
Kenya
3.4
87
Lesotho
1
94
Mali
3.1
104
Mozambique
4.8
106
Namibia
1.6
count
16
16
mean
4.5
2.58
std
2.54
2.06
min
1
0.7
25%
2.88
1.08
50%
3.8
1.45
75%
6.52
4.15
max
9.9
6.7
<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 25 to 160
Data columns (total 3 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Economy 16 non-null object
1 Percent of firms choosing customs and trade regulations as their biggest obstacle 16 non-null float64
2 Percent of firms choosing tax administration as their biggest obstacle 16 non-null float64
dtypes: float64(2), object(1)
memory usage: 512.0+ bytes
/shared-libs/python3.9/py/lib/python3.9/site-packages/seaborn/axisgrid.py:88: UserWarning: Tight layout not applied. tight_layout cannot make axes width small enough to accommodate all axes decorations
self._figure.tight_layout(*args, **kwargs)
count
16
16
mean
4.5
2.58
std
2.54
2.06
min
1
0.7
25%
2.88
1.08
50%
3.8
1.45
75%
6.52
4.15
max
9.9
6.7
/tmp/ipykernel_83/3147264411.py:4: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
combined_data['Response'] = response_var['2018'].values
25
Botswana
3.9
28
Burkina Faso
6.8
55
Ethiopia
9.9
59
Gabon
6.5
63
Ghana
6.6
81
Kenya
3.4
87
Lesotho
1
94
Mali
3.1
104
Mozambique
4.8
106
Namibia
1.6
Regression Analysis
coeffecient : [-1.28726747 1.78497867]
intercept: 26.9591732695924