mpl_to_plotly

# coding: utf-8

# In[1]:


from scipy.stats import sem
import pandas as pd
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


df = pd.read_csv("remittance-inflow.csv")


# In[3]:


df.head()


# In[4]:


india_data = df[df["Migrant remittance inflows (US$ million)"] == 'India']


# In[5]:


india_data = india_data.fillna(1)


# In[6]:


india_data["1970"]


# In[7]:


india_data.loc[:"1970"]


# In[8]:


col_list = india_data.columns[2:]


# In[9]:


india_data[col_list].iloc[0]


# In[10]:


india_data_s = india_data[col_list].iloc[0]


# In[99]:


x = india_data_s.index

x = x[:47]
x


# In[101]:


y = india_data_s.values
y = y[:47]


# In[102]:


x=x.astype('float64',copy=False)
y=y.astype('float64',copy=False)


# In[103]:


plt.plot(x,y)


# In[104]:


x


# In[105]:


india_data_s.rolling(window=5).mean()[:47].index
x= india_data_s.rolling(window=2).mean()[:47].index
y= india_data_s.rolling(window=2).mean()[:47].values


# In[107]:



fig = plt.figure(figsize=(14,8))
ax = plt.subplot(111)

plt.plot(x,y)
plt.xlim(1970,2016)
plt.ylim(0,75000)
t = plt.xticks(x,x,rotation='vertical',fontsize=12)
plt.fill_between(x,y+5000,y-5000,color='#3F5D7D')
plt.plot(x,y,color='white',lw=2)


# In[108]:


import plotly as pltly


# In[109]:


pltly.tools.set_credentials_file(username='zero_0',api_key='iTLrjreGKQBYDFnTpQgz')


# In[110]:


import plotly.tools as tls


# In[111]:


pltly_fig  = tls.mpl_to_plotly(fig)