def unbias(filename, outfile, email=False):
filenametxt = "resume.txt"
extract_text.extract(filename, filenametxt, "text")
name = recognizeName.recognizeName(filenametxt)
pos_size = find_name.find_name(filename, name)
overplay.overlay(filename, outfile, "bigredbox.pdf", *pos_size)
if (email):
emails = recognizeEmails.recognizeEmails(filenametxt)
print(emails)
for e in emails:
pos_size = find_name.find_name(filename, e)
overplay.overlay(outfile, outfile, "bigredbox.pdf", *pos_size)
import recognizeName
import recognizeEmails
import overplay
import find_name
import extract_text
filenamepdf = "sample_resumes/sample2.pdf"
filenametxt = "resume.txt"
extract_text.extract(filenamepdf, filenametxt, "text")
name = recognizeName.recognizeName(filenametxt)
print(name)
pos_size = find_name.find_name(filenamepdf, name)
overplay.overlay(filenamepdf, "bigredbox.pdf", *pos_size)
emails = recognizeEmails.recognizeEmails(filenametxt)
print(emails)
for e in emails:
pos_size = find_name.find_name(filenamepdf, e)
overplay.overlay("resume_unbiased.pdf", "bigredbox.pdf", *pos_size)
def app():
st.title("Welcome to T20I-cric-data!")
st.sidebar.title('Find Player Profile')
user_input_player = st.sidebar.text_input(
label="Enter Cricketer's Name Eg. (DA Warner)")
#user_input_player = st.sidebar.text_input(label="Enter Cricketer's Name Eg. (DA Warner)")
get_top_players = st.sidebar.checkbox(label="Get Top Players in the T20Is",
value=False)
if (not user_input_player) or (not get_top_players):
st.write(
"You can try putting a cricket player's name in the left panel to see his profile as well as visualise the data."
)
if user_input_player:
player_name = find_name(user_input_player, t20=True)
if player_name is None:
st.markdown('**' + user_input_player + '** ' + " is not found.")
else:
bat_bowl = st.sidebar.selectbox(label="Batting/Bowling Profile",
options=("bat", "bowl"))
bat = True
xaxis = 'season'
yaxis = 'Runs'
if bat_bowl == 'bowl':
bat = False
yaxis = 'Wickets'
year_from = st.sidebar.number_input("Year from",
min_value=2005,
max_value=2021,
value=2005,
step=1)
year_to = st.sidebar.number_input("Year to",
min_value=2005,
max_value=2021,
value=2021,
step=1)
visualize = st.sidebar.checkbox(label="Visualize", value=False)
st.markdown('**' + player_name + '**')
df = get_player_profile(player_name,
batsman=bat,
year_from=year_from,
year_to=year_to,
t20=True)
st.table(df)
if visualize:
numeric_cols = list(
df.select_dtypes(include=np.number).columns.values)
xaxis = st.sidebar.selectbox(label="x-axis",
options=numeric_cols)
yaxis = st.sidebar.selectbox(label="y-axis",
options=numeric_cols,
index=numeric_cols.index(yaxis))
fig = px.bar(df, x=xaxis,
y=yaxis) #, range_x=[year_from, year_to])
st.plotly_chart(fig)
elif get_top_players:
top_N = st.sidebar.number_input("Show Top ",
max_value=25,
value=10,
step=1)
cols = [
'Runs', 'Innings', 'NO', 'BF', 'HS', 'Ave', 'SR', '50s', '100s',
'4s', '6s'
]
sort_by = st.sidebar.selectbox(label="Sort By", options=cols)
df_top = top_players(sort_by=sort_by, topN=top_N)
st.markdown('**' + 'Top T20I batsmen sorted by ' + sort_by + '**' +
' (Cut Off Runs =1000)')
st.table(df_top)
#st.sidebar.title('Team Profile')
#all_ipl_teams=("Chennai Super Kings", "Delhi Capitals", "Punjab Kings", "Kolkata Knight Riders",
# "Mumbai Indians", "Rajasthan Royals", "Royal Challengers Bangalore", "Sunrisers Hyderabad")
#team_name = st.sidebar.selectbox(label="Team name",
# options=all_ipl_teams)
Footer()
def app():
st.title("Welcome to IPL-cric-data!")
st.sidebar.title('Find Player Profile')
user_input_player = st.sidebar.text_input(
label="Enter Cricketer's Name Eg. (Tendulkar)"
) #, value="SR Tendulkar")
if not user_input_player:
st.write(
"You can try putting a cricket player's name in the left panel to see his profile as well as visualise the data."
)
if user_input_player:
player_name = find_name(user_input_player, ipl=True)
#player_name = user_input_player
if player_name is None:
st.markdown('**' + user_input_player + '** ' + " is not found.")
else:
bat_bowl = st.sidebar.selectbox(label="Batting/Bowling Profile",
options=("bat", "bowl"))
bat = True
xaxis = 'season'
yaxis = 'Runs'
if bat_bowl == 'bowl':
bat = False
yaxis = 'Wickets'
year_from = st.sidebar.number_input("Year from",
min_value=2008,
max_value=2021,
value=2008,
step=1)
year_to = st.sidebar.number_input("Year to",
min_value=2008,
max_value=2021,
value=2021,
step=1)
visualize = st.sidebar.checkbox(label="Visualize", value=False)
st.markdown('**' + player_name + '**')
df = get_player_profile(player_name,
batsman=bat,
year_from=year_from,
year_to=year_to,
ipl=True)
st.table(df)
if visualize:
numeric_cols = list(
df.select_dtypes(include=np.number).columns.values)
xaxis = st.sidebar.selectbox(label="x-axis",
options=numeric_cols)
yaxis = st.sidebar.selectbox(label="y-axis",
options=numeric_cols,
index=numeric_cols.index(yaxis))
fig = px.bar(df, x=xaxis,
y=yaxis) #, range_x=[year_from, year_to])
st.plotly_chart(fig)
#st.sidebar.title('Team Profile')
#all_ipl_teams=("Chennai Super Kings", "Delhi Capitals", "Punjab Kings", "Kolkata Knight Riders",
# "Mumbai Indians", "Rajasthan Royals", "Royal Challengers Bangalore", "Sunrisers Hyderabad")
#team_name = st.sidebar.selectbox(label="Team name",
# options=all_ipl_teams)
Footer()
def unbias(filename):
filenametxt = "resume.txt"
extract_text.extract(filename, filenametxt, "text")
name = recognizeName.recognizeName(filenametxt)
pos_size = find_name.find_name(filename, name)
overplay.overlay(filenamepdf, "bigredbox.pdf", *pos_size)