Vladimir Emelianov
Vladimir Emelianov

Reputation: 91

Dropping rows while iterating through multiple Pandas dataframes

so I have a list of dataframes as such:

yldDF = [dem2y, dem5y, dem10y, dem30y]


    Unnamed: 0 BBK01.WT0202
4   2014-01-02         0.21
5   2014-01-03         0.21
6   2014-01-04            .
7   2014-01-05            .
8   2014-01-06         0.20
9   2014-01-07         0.21
10  2014-01-08         0.21
11  2014-01-09         0.23
12  2014-01-10         0.21
13  2014-01-11            .

Where each dataframe looks like the above. Now when I try to iterate through the dataframes to remove the "." in the second column it doesn't seem to work.

dem2y = pd.read_csv("0202.csv")
dem5y = pd.read_csv("0505.csv")
dem10y = pd.read_csv("1010.csv")
dem30y = pd.read_csv("3030.csv")

### Begin cleaning

yldDF = [dem2y, dem5y, dem10y, dem30y]

for i in yldDF: 

    i.drop(i.columns[2], axis = 1,inplace = True)
    i.drop(range(4),inplace=True)
    i = i[i[i.columns[1]].apply(lambda x: str(x)!=".")]

I've tried the last line on a single Dataframe and it seems to work perfectly fine, however when I try it as part of a loop it doesn't seem to have any effect. Is there something i'm missing here? Or could this be a bug?

Upvotes: 0

Views: 49

Answers (1)

Alex Fortin
Alex Fortin

Reputation: 2415

If the problem is that only i is getting modified, you could try this trick:

# Store your `pandas.DataFrame` in a dict
yldDict = {'dem2y': dem2y, 'dem5y': dem5y, 'dem10y': dem10y, 'dem30y': dem30y}

# Loop on the keys of the dict
for keys in yldDict.keys(): 
    df = yldDict.get(keys, 'error') # Get pandas.DataFrame from dict
    # Do the operation you need to do
    df.drop(df.columns[2], axis = 1, inplace = True)
    df.drop(range(4), inplace=True)
    df = df[df[df.columns[1]].apply(lambda x: str(x)!=".")]
    # Post to dict
    yldDict[keys] = df

# Extract from dict
dem2y, dem5y, dem10y, dem30y = yldDict['dem2y'], yldDict['dem5y'], yldDict['dem10y'], yldDict['dem30y']
# Delete dict
del yldDict

Upvotes: 1

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