Concave Function to Interpolate Stocks Data

concave_function.py

# Function to input NA in column date
def imput_date(df:pd.DataFrame,col:'Date'):
    start = datetime.datetime.strptime(df.loc[0,col],'%Y-%m-%d')
    end = datetime.datetime.strptime(df.loc[df.shape[0] - 1,col],'%Y-%m-%d')
    list_date = pd.date_range(start,end).strftime('%Y-%m-%d').tolist()
    pd_date = pd.DataFrame(df,list_date)
    pd_date[col] = pd_date.index.astype(object)
    pd_date = pd_date.reset_index(drop=True)
    df_date = pd.merge(pd_date[col],df,on=col,how='left')
    return df_date

# Function to calculate return of stocks
def return_stocks(df:pd.DataFrame,col:'Adj Close',date:'Date'):
    df_no_na = df.dropna().reset_index(drop=True)
    return_data = [0]
    index_data = list(df_no_na.index)
    for i in range(1,len(index_data)):
        return_i = (df_no_na[col][index_data[i]] - 
                    df_no_na[col][index_data[i-1]])/df_no_na[col][index_data[i]]
        return_data.append(return_i)
    df_no_na = pd.concat([df_no_na[date],pd.DataFrame(return_data)],axis=1)
    df_full = pd.merge(df,df_no_na,on=date,how='left')
    df_full = df_full.rename(columns = {0:'Return'})
    return df_full

# Curve function
def curve_function(df):
    for i in df.columns:
        while df[i].isna().sum() > 0:
            for j in range(df.shape[0]):
                if pd.isnull(df.loc[j,i]):
                    seq_k = [j]
                    k = j
                    while pd.isnull(df.loc[k,i]):
                        k = k + 1
                        seq_k.append(k)
                    if len(seq_k) % 2 == 0:
                        df.loc[seq_k[int((len(seq_k) - 1)/2)],i] = (df.loc[j - 1,i] + df.loc[seq_k[len(seq_k) - 1],i])/2
                    else:
                        df.loc[seq_k[int((len(seq_k) - 1)/2)],i] = (df.loc[j - 1,i] + df.loc[seq_k[len(seq_k) - 1],i])/2
                else:
                    df.loc[j,i] = df.loc[j,i]
    return(df)