Skip to content

Commit

Permalink
updated syntax
Browse files Browse the repository at this point in the history
  • Loading branch information
@rohanjha123
rohanjha123 committed Apr 8, 2024
1 parent 72cada2 commit 2589c00
Show file tree
Hide file tree
Showing 2 changed files with 218 additions and 202 deletions.
210 changes: 109 additions & 101 deletions content/01-python_v_stata/.ipynb_checkpoints/syntax-checkpoint.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -506,105 +506,6 @@
"Below, we discuss all the features currently supported by `Stata2Python`, along with providing example usages."
]
},
{
"cell_type": "markdown",
"id": "d9ace3e5-b5e7-473e-8bdb-cf6559c2fcc1",
"metadata": {},
"source": [
"#### T-tests\n",
"\n",
"This function helps users determine the code for running [t-tests](https://www.jmp.com/en_us/statistics-knowledge-portal/t-test.html) in Python. Examples include:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "b48ee104-aa0a-4461-a1bc-9f40c6c90996",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(df['guard'])\n",
"df_1 = df[df['guard'] == catvar_vals[0]]\n",
"df_2 = df[df['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=True, nan_policy='propagate')\n"
]
}
],
"source": [
"stata2python(\"ttest wage, by(guard)\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "87876a2e-0b2c-40d5-a64a-c8ec25941aa1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(nba['guard'])\n",
"df_1 = nba[nba['guard'] == catvar_vals[0]]\n",
"df_2 = nba[nba['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=False, nan_policy='propagate')\n"
]
}
],
"source": [
"stata2python(\"ttest wage, by(guard) unequal\", \"nba\")"
]
},
{
"cell_type": "markdown",
"id": "89b477e9-82df-43d2-bc97-dc466c1bcb92",
"metadata": {},
"source": [
"Assuming you have all the correct packages installed, you can directly copy paste this code to see the output. For example, "
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "a485ec9f-25f6-4c24-9ee8-380b751ef6a1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"TtestResult(statistic=2.1432820571177977, pvalue=0.03299634994484977, df=266.3682612357414)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(nba['guard'])\n",
"df_1 = nba[nba['guard'] == catvar_vals[0]]\n",
"df_2 = nba[nba['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=False, nan_policy='propagate')"
]
},
{
"cell_type": "markdown",
"id": "bcac0225-7131-4a7d-9997-47958c10c172",
Expand Down Expand Up @@ -658,7 +559,7 @@
"id": "9357b734-d25a-4008-b0c9-86240daecff2",
"metadata": {},
"source": [
"Copy-pasting the output into Python to verify it works."
"Assuming you have all the correct packages installed, you can directly copy paste this code to see the output. For example, "
]
},
{
Expand Down Expand Up @@ -1049,6 +950,14 @@
"stata2python(\"describe\",\"nba\")"
]
},
{
"cell_type": "markdown",
"id": "6b4f8ca6-2d2f-4cdd-8bb4-89cef1d52631",
"metadata": {},
"source": [
"Verifying that the output works:"
]
},
{
"cell_type": "code",
"execution_count": 30,
Expand Down Expand Up @@ -1326,7 +1235,7 @@
}
],
"source": [
"import pandas as pd # Verifying that the output works\n",
"import pandas as pd \n",
"nba.describe()"
]
},
Expand Down Expand Up @@ -1541,6 +1450,105 @@
"pollution.hist(column='co2pc',bins=80);"
]
},
{
"cell_type": "markdown",
"id": "d9ace3e5-b5e7-473e-8bdb-cf6559c2fcc1",
"metadata": {},
"source": [
"#### T-tests\n",
"\n",
"This function helps users determine the code for running [t-tests](https://www.jmp.com/en_us/statistics-knowledge-portal/t-test.html) in Python. Examples include:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "b48ee104-aa0a-4461-a1bc-9f40c6c90996",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(df['guard'])\n",
"df_1 = df[df['guard'] == catvar_vals[0]]\n",
"df_2 = df[df['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=True, nan_policy='propagate')\n"
]
}
],
"source": [
"stata2python(\"ttest wage, by(guard)\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "87876a2e-0b2c-40d5-a64a-c8ec25941aa1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(nba['guard'])\n",
"df_1 = nba[nba['guard'] == catvar_vals[0]]\n",
"df_2 = nba[nba['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=False, nan_policy='propagate')\n"
]
}
],
"source": [
"stata2python(\"ttest wage, by(guard) unequal\", \"nba\")"
]
},
{
"cell_type": "markdown",
"id": "89b477e9-82df-43d2-bc97-dc466c1bcb92",
"metadata": {},
"source": [
"Verifying that the output works:"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "a485ec9f-25f6-4c24-9ee8-380b751ef6a1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"TtestResult(statistic=2.1432820571177977, pvalue=0.03299634994484977, df=266.3682612357414)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy import stats\n",
"### First, we must filter the DataFrame to obtain the right values\n",
"catvar_vals = np.unique(nba['guard'])\n",
"df_1 = nba[nba['guard'] == catvar_vals[0]]\n",
"df_2 = nba[nba['guard'] == catvar_vals[1]]\n",
"### Then, we can run our t-test\n",
"stats.ttest_ind(df_1['wage'], df_2['wage'], equal_var=False, nan_policy='propagate')"
]
},
{
"cell_type": "markdown",
"id": "14245a39-b06f-406b-a597-fc4ffcffead0",
Expand Down
Loading

0 comments on commit 2589c00

Please sign in to comment.