Seed for the random number generator. Default is 1234.
1234
beta_type
str
Type of beta coefficients. Must be one of ‘1’, ‘2’, or ‘3’. Default is ‘1’.
'1'
error_type
str
Type of error term. Must be one of ‘1’, ‘2’, or ‘3’. Default is ‘1’.
'1'
model
str
Type of the DGP. Must be either ‘Feols’ or ‘Fepois’. Default is ‘Feols’.
'Feols'
Returns
Name
Type
Description
pandas.DataFrame
A pandas DataFrame with simulated data.
Raises
Name
Type
Description
ValueError
If beta_type is not ‘1’, ‘2’, or ‘3’, or if error_type is not ‘1’, ‘2’, or ‘3’, or if model is not ‘Feols’ or ‘Fepois’.
Examples
import pyfixest as pfdata = pf.get_data()data.head()
Y
Y2
X1
X2
f1
f2
f3
group_id
Z1
Z2
weights
0
NaN
2.357103
0.0
0.457858
15.0
0.0
7.0
9.0
-0.330607
1.054826
0.661478
1
-1.458643
5.163147
NaN
-4.998406
6.0
21.0
4.0
8.0
NaN
-4.113690
0.772732
2
0.169132
0.751140
2.0
1.558480
NaN
1.0
7.0
16.0
1.207778
0.465282
0.990929
3
3.319513
-2.656368
1.0
1.560402
1.0
10.0
11.0
3.0
2.869997
0.467570
0.021123
4
0.134420
-1.866416
2.0
-3.472232
19.0
20.0
6.0
14.0
0.835819
-3.115669
0.790815
The data set contains a continuous outcome Y, covariates X1 and X2, fixed effects f1, f2 and f3, an instrument Z1, and some missing values. Set model="Fepois" for a count outcome.
pf.get_data(model="Fepois")["Y"].head()
0 NaN
1 0.0
2 2.0
3 0.0
4 2.0
Name: Y, dtype: float64