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alvarobartt/identify_all_trends.py

Last active February 4, 2023 10:00
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  1. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. 1 changed file with 30 additions and 30 deletions.
    60 changes: 30 additions & 30 deletions identify_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -6,45 +6,45 @@
    sns.set(style='darkgrid')

    df = trendet.identify_trends(equity='bbva',
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])

    df.reset_index(inplace=True)

    with plt.style.context('paper'):
    plt.figure(figsize=(20, 10))
    plt.figure(figsize=(20, 10))

    ax = sns.lineplot(x=df['Date'], y=df['Close'])
    ax = sns.lineplot(x=df['Date'], y=df['Close'])

    values = list()
    values = list()

    value = {
    'trend': 'Up Trend',
    'color': 'green',
    }
    value = {
    'trend': 'Up Trend',
    'color': 'green',
    }

    values.append(value)
    values.append(value)

    value = {
    'trend': 'Down Trend',
    'color': 'red',
    }
    value = {
    'trend': 'Down Trend',
    'color': 'red',
    }

    values.append(value)
    values.append(value)

    for label in ['A', 'B', 'C']:
    for value in values:
    sns.lineplot(x=df[df[value['trend']] == label]['Date'],
    y=df[df[value['trend']] == label]['Close'],
    color=value['color'])

    ax.axvspan(df[df[value['trend']] == label]['Date'].iloc[0],
    df[df[value['trend']] == label]['Date'].iloc[-1],
    alpha=0.1,
    color=value['color'])
    for label in ['A', 'B', 'C']:
    for value in values:
    sns.lineplot(x=df[df[value['trend']] == label]['Date'],
    y=df[df[value['trend']] == label]['Close'],
    color=value['color'])

    plt.show()
    ax.axvspan(df[df[value['trend']] == label]['Date'].iloc[0],
    df[df[value['trend']] == label]['Date'].iloc[-1],
    alpha=0.1,
    color=value['color'])

    plt.show()
  2. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. 1 changed file with 23 additions and 23 deletions.
    46 changes: 23 additions & 23 deletions identify_df_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -9,40 +9,40 @@

    test = investpy.get_historical_data(equity='repsol',
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019')
    from_date='01/01/2018',
    to_date='01/01/2019')

    res = identify_df_trends(df=test, column='Close')

    res.reset_index(inplace=True)

    with plt.style.context('paper'):
    plt.figure(figsize=(20, 10))
    plt.figure(figsize=(20, 10))

    ax = sns.lineplot(x=res['Date'], y=res['Close'])
    ax = sns.lineplot(x=res['Date'], y=res['Close'])

    labels = res['Up Trend'].dropna().unique().tolist()
    labels = res['Up Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=res[res['Up Trend'] == label]['Date'],
    y=res[res['Up Trend'] == label]['Close'],
    color='green')
    for label in labels:
    sns.lineplot(x=res[res['Up Trend'] == label]['Date'],
    y=res[res['Up Trend'] == label]['Close'],
    color='green')

    ax.axvspan(res[res['Up Trend'] == label]['Date'].iloc[0],
    res[res['Up Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='green')
    ax.axvspan(res[res['Up Trend'] == label]['Date'].iloc[0],
    res[res['Up Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='green')

    labels = res['Down Trend'].dropna().unique().tolist()
    labels = res['Down Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=res[res['Down Trend'] == label]['Date'],
    y=res[res['Down Trend'] == label]['Close'],
    color='red')
    for label in labels:
    sns.lineplot(x=res[res['Down Trend'] == label]['Date'],
    y=res[res['Down Trend'] == label]['Close'],
    color='red')

    ax.axvspan(res[res['Down Trend'] == label]['Date'].iloc[0],
    res[res['Down Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='red')
    ax.axvspan(res[res['Down Trend'] == label]['Date'].iloc[0],
    res[res['Down Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='red')

    plt.show()
    plt.show()
  3. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. No changes.
  4. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. 1 changed file with 1 addition and 1 deletion.
    2 changes: 1 addition & 1 deletion identify_df_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -8,7 +8,7 @@
    sns.set(style='darkgrid')

    test = investpy.get_historical_data(equity='repsol',
    country='spain',
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019')

  5. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. No changes.
  6. Álvaro Bartolomé del Canto revised this gist Sep 16, 2019. 3 changed files with 63 additions and 7 deletions.
    1 change: 1 addition & 0 deletions identify_all_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -6,6 +6,7 @@
    sns.set(style='darkgrid')

    df = identify_all_trends(equity='bbva',
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5)
    48 changes: 48 additions & 0 deletions identify_df_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,48 @@
    import trendet

    import investpy

    import matplotlib.pyplot as plt
    import seaborn as sns

    sns.set(style='darkgrid')

    test = investpy.get_historical_data(equity='repsol',
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019')

    res = identify_df_trends(df=test, column='Close')

    res.reset_index(inplace=True)

    with plt.style.context('paper'):
    plt.figure(figsize=(20, 10))

    ax = sns.lineplot(x=res['Date'], y=res['Close'])

    labels = res['Up Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=res[res['Up Trend'] == label]['Date'],
    y=res[res['Up Trend'] == label]['Close'],
    color='green')

    ax.axvspan(res[res['Up Trend'] == label]['Date'].iloc[0],
    res[res['Up Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='green')

    labels = res['Down Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=res[res['Down Trend'] == label]['Date'],
    y=res[res['Down Trend'] == label]['Close'],
    color='red')

    ax.axvspan(res[res['Down Trend'] == label]['Date'].iloc[0],
    res[res['Down Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='red')

    plt.show()
    21 changes: 14 additions & 7 deletions identify_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -6,11 +6,12 @@
    sns.set(style='darkgrid')

    df = trendet.identify_trends(equity='bbva',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])
    country='spain',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])

    df.reset_index(inplace=True)

    @@ -37,7 +38,13 @@

    for label in ['A', 'B', 'C']:
    for value in values:
    sns.lineplot(x=df[df[value['trend']] == label]['Date'], y=df[df[value['trend']] == label]['Close'], color=value['color'])
    ax.axvspan(df[df[value['trend']] == label]['Date'].iloc[0], df[df[value['trend']] == label]['Date'].iloc[-1], alpha=0.1, color=value['color'])
    sns.lineplot(x=df[df[value['trend']] == label]['Date'],
    y=df[df[value['trend']] == label]['Close'],
    color=value['color'])

    ax.axvspan(df[df[value['trend']] == label]['Date'].iloc[0],
    df[df[value['trend']] == label]['Date'].iloc[-1],
    alpha=0.1,
    color=value['color'])

    plt.show()
  7. Álvaro Bartolomé del Canto revised this gist Aug 23, 2019. 2 changed files with 44 additions and 0 deletions.
    44 changes: 44 additions & 0 deletions identify_all_trends.py
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,44 @@
    import trendet

    import matplotlib.pyplot as plt
    import seaborn as sns

    sns.set(style='darkgrid')

    df = identify_all_trends(equity='bbva',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5)

    df.reset_index(inplace=True)

    with plt.style.context('paper'):
    plt.figure(figsize=(20, 10))

    ax = sns.lineplot(x=df['Date'], y=df['Close'])

    labels = df['Up Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=df[df['Up Trend'] == label]['Date'],
    y=df[df['Up Trend'] == label]['Close'],
    color='green')

    ax.axvspan(df[df['Up Trend'] == label]['Date'].iloc[0],
    df[df['Up Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='green')

    labels = df['Down Trend'].dropna().unique().tolist()

    for label in labels:
    sns.lineplot(x=df[df['Down Trend'] == label]['Date'],
    y=df[df['Down Trend'] == label]['Close'],
    color='red')

    ax.axvspan(df[df['Down Trend'] == label]['Date'].iloc[0],
    df[df['Down Trend'] == label]['Date'].iloc[-1],
    alpha=0.2,
    color='red')

    plt.show()
    0 trendet.py → identify_trends.py
    View file
    File renamed without changes.
  8. Álvaro Bartolomé del Canto revised this gist Aug 22, 2019. 1 changed file with 5 additions and 5 deletions.
    10 changes: 5 additions & 5 deletions trendet.py
    View file
    Original file line number Diff line number Diff line change
    @@ -6,11 +6,11 @@
    sns.set(style='darkgrid')

    df = trendet.identify_trends(equity='bbva',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])

    df.reset_index(inplace=True)

  9. Álvaro Bartolomé del Canto created this gist Aug 22, 2019.
    43 changes: 43 additions & 0 deletions trendet.py
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,43 @@
    import trendet

    import matplotlib.pyplot as plt
    import seaborn as sns

    sns.set(style='darkgrid')

    df = trendet.identify_trends(equity='bbva',
    from_date='01/01/2018',
    to_date='01/01/2019',
    window_size=5,
    trend_limit=3,
    labels=['A', 'B', 'C'])

    df.reset_index(inplace=True)

    with plt.style.context('paper'):
    plt.figure(figsize=(20, 10))

    ax = sns.lineplot(x=df['Date'], y=df['Close'])

    values = list()

    value = {
    'trend': 'Up Trend',
    'color': 'green',
    }

    values.append(value)

    value = {
    'trend': 'Down Trend',
    'color': 'red',
    }

    values.append(value)

    for label in ['A', 'B', 'C']:
    for value in values:
    sns.lineplot(x=df[df[value['trend']] == label]['Date'], y=df[df[value['trend']] == label]['Close'], color=value['color'])
    ax.axvspan(df[df[value['trend']] == label]['Date'].iloc[0], df[df[value['trend']] == label]['Date'].iloc[-1], alpha=0.1, color=value['color'])

    plt.show()