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Fix empty equity report #3739

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merged 8 commits into from
Dec 13, 2022
Merged

Fix empty equity report #3739

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e1dc01a
handle empty dfs
montezdesousa Dec 9, 2022
a2c302d
handle empty dfs
montezdesousa Dec 9, 2022
6c9b6e0
Merge branch 'main' into empty_reports
montezdesousa Dec 9, 2022
6039e4f
black
montezdesousa Dec 9, 2022
2cc6c25
Merge branch 'main' into empty_reports
montezdesousa Dec 12, 2022
3fd1127
fix equity report
montezdesousa Dec 12, 2022
c0fc16c
msft
montezdesousa Dec 12, 2022
23dbf4a
Merge branch 'main' into empty_reports
jmaslek Dec 12, 2022
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104 changes: 58 additions & 46 deletions openbb_terminal/reports/templates/equity.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -257,23 +257,23 @@
"outputs": [],
"source": [
"df_analyst = openbb.stocks.dd.analyst(symbol=symbol)\n",
"print(df_analyst.columns)\n",
"\n",
"if not df_analyst.empty:\n",
" if \"target\" in df_analyst.columns:\n",
" if \"target_to\" in df_analyst.columns:\n",
" df_analyst[\"target\"] = df_analyst[\"target_to\"].combine_first(\n",
" df_analyst[\"target\"]\n",
" )\n",
" else:\n",
" df_analyst[\"target\"] = df_analyst[\"target_to\"]\n",
" df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
" columns={\n",
" \"category\": \"Category\",\n",
" \"analyst\": \"Analyst\",\n",
" \"rating\": \"Rating\",\n",
" \"target\": \"Price Target\",\n",
" }\n",
" )\n",
" else:\n",
" df_analyst[\"target\"] = df_analyst[\"target_to\"]\n",
" df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
" columns={\n",
" \"category\": \"Category\",\n",
" \"analyst\": \"Analyst\",\n",
" \"rating\": \"Rating\",\n",
" \"target\": \"Price Target\",\n",
" }\n",
" )\n",
"df_analyst"
]
},
Expand Down Expand Up @@ -811,16 +811,17 @@
"import pandas as pd\n",
"\n",
"df_insider = pd.DataFrame.from_dict(openbb.stocks.ins.lins(symbol=symbol)).head(10)\n",
"df_insider[\"Val ($)\"] = df_insider[\"Value ($)\"].replace({\",\": \"\"}, regex=True)\n",
"df_insider[\"Trade\"] = df_insider.apply(\n",
" lambda row: (-1 * float(row[\"Val ($)\"]))\n",
" if row[\"Transaction\"] == \"Sale\"\n",
" else (float(row[\"Val ($)\"]) if row[\"Transaction\"] == \"Buy\" else 0),\n",
" axis=1,\n",
")\n",
"last_10_insider_trading = round(sum(df_insider[\"Trade\"]) / 1_000_000, 2)\n",
"df_insider = df_insider.drop(columns=[\"Val ($)\", \"Trade\"])\n",
"df_insider"
"if not df_insider.empty:\n",
" df_insider[\"Val ($)\"] = df_insider[\"Value ($)\"].replace({\",\": \"\"}, regex=True)\n",
" df_insider[\"Trade\"] = df_insider.apply(\n",
" lambda row: (-1 * float(row[\"Val ($)\"]))\n",
" if row[\"Transaction\"] == \"Sale\"\n",
" else (float(row[\"Val ($)\"]) if row[\"Transaction\"] == \"Buy\" else 0),\n",
" axis=1,\n",
" )\n",
" last_10_insider_trading = round(sum(df_insider[\"Trade\"]) / 1_000_000, 2)\n",
" df_insider = df_insider.drop(columns=[\"Val ($)\", \"Trade\"])\n",
" df_insider"
]
},
{
Expand Down Expand Up @@ -953,10 +954,11 @@
"income_df = openbb.stocks.fa.income(symbol, source=\"YahooFinance\")\n",
"data_df = openbb.stocks.fa.data(symbol)\n",
"mgmt_df = openbb.stocks.fa.mgmt(symbol)\n",
"mgmt_df[\"Info\"] = mgmt_df[\"Info\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
"mgmt_df[\"Insider Activity\"] = mgmt_df[\"Insider Activity\"].apply(\n",
" lambda x: f'<a href=\"{x}\">{x}</a>' if x != \"-\" else x\n",
")\n",
"if not mgmt_df.empty:\n",
" mgmt_df[\"Info\"] = mgmt_df[\"Info\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
" mgmt_df[\"Insider Activity\"] = mgmt_df[\"Insider Activity\"].apply(\n",
" lambda x: f'<a href=\"{x}\">{x}</a>' if x != \"-\" else x\n",
" )\n",
"try:\n",
" hist_dcf = openbb.stocks.fa.dcf(symbol)\n",
"except:\n",
Expand Down Expand Up @@ -1152,14 +1154,17 @@
" [\"RSI level is oversold\", \"RSI level is normal\", \"RSI level is overbought\"],\n",
" rsi_value,\n",
")\n",
"htmlcode += widgets.kpi(\n",
" [0],\n",
" [\n",
" \"The sum of last 10 insider trading (in millions) was negative\",\n",
" \"The sum of last 10 insider trading (in millions) was positive\",\n",
" ],\n",
" last_10_insider_trading,\n",
")\n",
"try:\n",
" htmlcode += widgets.kpi(\n",
" [0],\n",
" [\n",
" \"The sum of last 10 insider trading (in millions) was negative\",\n",
" \"The sum of last 10 insider trading (in millions) was positive\",\n",
" ],\n",
" last_10_insider_trading,\n",
" )\n",
"except:\n",
" pass\n",
"htmlcode += widgets.kpi(\n",
" [-0.1, 0.1],\n",
" [\n",
Expand Down Expand Up @@ -1201,9 +1206,11 @@
" )\n",
"except:\n",
" pass\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, f\"Management team of {symbol}\") + mgmt_df.to_html(escape=False)]\n",
")\n",
"\n",
"if not mgmt_df.empty:\n",
" htmlcode += widgets.row(\n",
" [widgets.h(3, f\"Management team of {symbol}\") + mgmt_df.to_html(escape=False)]\n",
" )\n",
"body += widgets.add_tab(\"Overview\", htmlcode)\n",
"\n",
"htmlcode = widgets.row([widgets.h(3, \"Price Target Chart\") + price_target_chart])\n",
Expand All @@ -1229,12 +1236,15 @@
" )\n",
"except:\n",
" pass\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, \"Earnings\") + df_quarter_earnings.head().to_html()]\n",
")\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, \"Revenues\") + df_quarter_revenues.head().to_html()]\n",
")\n",
"\n",
"if not df_quarter_earnings.empty:\n",
" htmlcode += widgets.row(\n",
" [widgets.h(3, \"Earnings\") + df_quarter_earnings.head().to_html()]\n",
" )\n",
"if not df_quarter_revenues.empty:\n",
" htmlcode += widgets.row(\n",
" [widgets.h(3, \"Revenues\") + df_quarter_revenues.head().to_html()]\n",
" )\n",
"try:\n",
" htmlcode += widgets.row(\n",
" [\n",
Expand Down Expand Up @@ -1365,14 +1375,16 @@
"htmlcode += widgets.row([adx_chart])\n",
"body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
"\n",
"try:\n",
"if not df_insider.empty:\n",
" htmlcode = widgets.row(\n",
" [widgets.h(3, \"Last Activity\") + df_insider.head(10).to_html(col_space=\"75px\")]\n",
" )\n",
"except:\n",
" pass\n",
"else:\n",
" htmlcode = widgets.row([widgets.h(3, \"Last Activity\") + widgets.p(\"No insider trading data found.\")])\n",
"\n",
"body += widgets.add_tab(\"Insider Trading\", htmlcode)\n",
"\n",
"\n",
"htmlcode = widgets.row([bw_year])\n",
"htmlcode += widgets.row([bw_month])\n",
"body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
Expand Down Expand Up @@ -1456,7 +1468,7 @@
},
"vscode": {
"interpreter": {
"hash": "cb66ba39c97f15743fbb79e204a841ea03600987d49579cfb0ffc8e8dd934c69"
"hash": "e784374cc4f9a84ed6af2983247aaf351b155c82bcc2188134a65f3c99031000"
}
}
},
Expand Down
46 changes: 25 additions & 21 deletions openbb_terminal/stocks/due_diligence/business_insider_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -194,27 +194,31 @@ def get_estimates(symbol: str) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame
)
# df_quarter_revenues.index.name = 'Revenues'

l_quarter = list()
l_date = list()
for quarter_title in df_quarter_earnings.columns:
l_quarter.append(re.split(" ending", quarter_title)[0])
if len(re.split(" ending", quarter_title)) == 2:
l_date.append("ending " + re.split(" ending", quarter_title)[1].strip())
else:
l_date.append("-")

df_quarter_earnings.index.name = "QUARTER EARNINGS ESTIMATES"
df_quarter_earnings.columns = l_quarter
df_quarter_earnings.loc["Date"] = l_date
df_quarter_earnings = df_quarter_earnings.reindex(
["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
)
if not df_quarter_earnings.empty:
l_quarter = list()
l_date = list()
for quarter_title in df_quarter_earnings.columns:
l_quarter.append(re.split(" ending", quarter_title)[0])
if len(re.split(" ending", quarter_title)) == 2:
l_date.append(
"ending " + re.split(" ending", quarter_title)[1].strip()
)
else:
l_date.append("-")

df_quarter_earnings.index.name = "QUARTER EARNINGS ESTIMATES"
df_quarter_earnings.columns = l_quarter
df_quarter_earnings.loc["Date"] = l_date
df_quarter_earnings = df_quarter_earnings.reindex(
["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
)

df_quarter_revenues.index.name = "QUARTER REVENUES ESTIMATES"
df_quarter_revenues.columns = l_quarter
df_quarter_revenues.loc["Date"] = l_date
df_quarter_revenues = df_quarter_revenues.reindex(
["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
)
if not df_quarter_revenues.empty:
df_quarter_revenues.index.name = "QUARTER REVENUES ESTIMATES"
df_quarter_revenues.columns = l_quarter
df_quarter_revenues.loc["Date"] = l_date
df_quarter_revenues = df_quarter_revenues.reindex(
["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
)

return df_year_estimates, df_quarter_earnings, df_quarter_revenues
3 changes: 2 additions & 1 deletion openbb_terminal/stocks/due_diligence/finviz_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,8 @@ def get_analyst_data(symbol: str) -> pd.DataFrame:
"""
d_finviz_analyst_price = get_analyst_price_targets_workaround(symbol)
df_fa = pd.DataFrame.from_dict(d_finviz_analyst_price)
df_fa.set_index("date", inplace=True)
if not df_fa.empty:
df_fa.set_index("date", inplace=True)

return df_fa

Expand Down
1 change: 1 addition & 0 deletions openbb_terminal/stocks/fundamental_analysis/yahoo_finance_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -436,6 +436,7 @@ def get_financials(symbol: str, statement: str, ratios: bool = False) -> pd.Data
df.replace("-", np.nan, inplace=True)
df = df.dropna(how="all")
df = df.replace(",", "", regex=True)
df = df.replace("k", "", regex=True)
df = df.astype("float")

# Data except EPS is returned in thousands, convert it
Expand Down
27 changes: 14 additions & 13 deletions openbb_terminal/stocks/insider/finviz_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,21 +28,22 @@ def get_last_insider_activity(symbol: str) -> pd.DataFrame:
"""
activity_dict = finviz.get_insider(symbol)
df = pd.DataFrame.from_dict(activity_dict)
df.set_index("Date", inplace=True)
df = df[
[
"Relationship",
"Transaction",
"#Shares",
"Cost",
"Value ($)",
"#Shares Total",
"Insider Trading",
"SEC Form 4",
]
]

if df.empty:
console.print(f"[red]No insider information found for {symbol}.\n[/red]")
else:
df.set_index("Date", inplace=True)
df = df[
[
"Relationship",
"Transaction",
"#Shares",
"Cost",
"Value ($)",
"#Shares Total",
"Insider Trading",
"SEC Form 4",
]
]

return df