Pandas dataframe .at ValueError : cannot convert string to float

Question

I'm trying to fill in value for a specific cell in a dataframe that already has some info in it. When I test it with small data it works but in my project it throws "ValueError : cannot convert string to float"

# df : a dataframe with data to be extracted and added to another dataframe data

some_list = df.iloc[:, 0].values
values = df.iloc[:, 1].values

indexList = data.index.values.tolist()

index = 0
for x in some_list:
    s = values[index]
    if x in indexList:
        # this line raised ValueError : cannot convert __(values in s)__ from string to float
        data.at[x, 'Some Column'] = s
    index += 1

elements in some_list and values are strings. Here the existing dataframe is data, where one of the column is 'Some Column', and index labels are some elements in some_list (therefore if the current element x in some_list is one of the index label, set value at the cell (row : index label x, column : 'Some Column' ) to values[the same row that this x is found]

before filling in cells under 'Some Column' should be NaN

A small sample I tried testing the .at function with (that didn't raised valueError):

column=['Year', 'first', 'second', 'third']
s = 'label1'
data = pd.DataFrame(columns=column)
row = pd.Series({'Year' : 2019, 'first' : 'asa', 'second' : 'awdqw'}, name=s)
data = data.append(row)


# Creates a pandas DataFrame. 
data_snip = {'name':['A', 'B', 'C', 'D'], 'y':[1, 2, 3, 4]} 
df = pd.DataFrame(data_snip, index =['one', 'two', 'three', 'four'])
df_array = df.iloc[:, 0].values
s = df_array[3] # should be 'D'

s = 'label3'
row = pd.Series({'Year' : 2030, 'first' : 'ubeubf', 'second' : 'qov.z'}, name=s)
data = data.append(row)
data.at['label3', 'third'] = s

and this is what data looks like :

        Year   first second third
label1  2019     asa  awdqw   NaN
label3  2030  ubeubf  qov.z     D

Any help would be greatly appreciated !!

Georgina Skibinski · Accepted Answer · 2019-12-29 22:19:56Z

4

Check df.dtypes - your error is coming from the fact, that you are trying to pack string object into column with dtype float. .at[] doesn't do any auto casting of column type.

Before assigning string to a cell, make sure it's of object dtype:

import pandas as pd

import numpy as np

df=pd.DataFrame(data={"x": list("abc"), "y": [1,2,3], "z": [np.nan for i in range(3)]}, index=["p", "q", "r"])

print(df)
#this works fine:
df.at["r", "z"]=4.5

print(df)
#without the line below it will fail:
df["z"]=df["z"].astype(str)
df.at["q", "z"]="z"

answered Dec 29, 2019 at 22:19

Georgina Skibinski

13.5k2 gold badges16 silver badges44 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Pandas dataframe .at ValueError : cannot convert string to float

1 Answer 1

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related